Running DOOM Conventionally, But… Delivery/Installation, Not So Much

Incorrigible repeat readers of this Crummy Little Blog That Nobody Reads (CLBTNR) know that we’ve mentioned previously the craze of running the first-person shooter DOOM on unconventional platforms. The most recent instance was running it in a PDF file ^[1], apparently using an embedded scripting language.

Embedded scripting languages are, as a rule, evil. Data files and programs should be kept as separate as possible. Though, that’s often not very separate.

Today comes news that DOOM can be run on conventional hardware, but distributed, installed, and run by decidedly unconventional means:

That’s pointing at an article on the blog of infrastructure and security engineer Adam Rice. ^[2]

A bit of background:

• DNS, or the Domain Name System, is an internet protocol that dates in its current from from RFC-1035 back in November of 1987. It’s a system for mapping host names for computers (like “www.someweekendreading.blog”) to IP addresses (things like “185.199.108.153”) that can actually be used to route network packets.

  The data is stored on many computers world-wide.

• DNS can also be used to distribute other kinds of data, mostly for normal purposes. Though, again as incorrigible CLBTNR readers know, it can be used to distribute silly things as well, like the lyrics to the “Bad Horse” song in Dr. Horrible’s Sing-Along Blog. ^[3]

• Rice is a fan of using DNS to poke security holes in networks:

  If you’ve ever poked at one of my CTF challenges, you’ve probably noticed a pattern - I love hiding payloads in TXT DNS records. I stash the malicious code in a TXT record, have the implant query for it at runtime, and now suddenly the payload is being delivered by the same infrastructure that resolves grandmas-cookie-recipes.com. It’s trivially easy to set up and surprisingly annoying to catch forensically, because who’s flagging the historic contents of TXT records?

• If you’re familiar with the ways of computer-touchers, you can pretty much write the rest of the story. For everybody else, here’s what he did:

  The universal benchmark for “can this thing do something it was never designed to do?” is, always has been, and always will be DOOM. Thermostats run DOOM, pregnancy tests run DOOM, and I want DNS to run DOOM.

• He found a C# port of DOOM. C# can be run on things called managed .NET assemblies. It’s not important exactly what that is, except for 2 facts:
  • They’re on almost all reasonably recent Windows machines, and are not too uncommon on Linux and Mac machines. So there’s wide availability.
  • The “managed” part means bytes can be loaded from a stream to the net, and no data ever need touch a file on a tightly controlled corporate disk.

Ok, so you divide the C# DOOM binaries into about 2,000 pieces of about 2,000 characters each, given them serial numbers for reassembly in the correct order, and upload them as part of the DNS info for a host you control.

Result: A script tiny enough to be typed from memory can “download” DOOM from the DNS system, evading most network security on hosts where DOOM has no business, and be played on a computer which is supposed to be game-free.

Rice’s description:

I described this project to my mother as such: It’s like taking a phone book and playing the 1986 academy award winning action film Top Gun starring Tom Cruise as a flip-book animation out of the phone numbers on every page.

Within minutes, the de rigeur meme appeared, as shown here. (Is that always a Cuban flag patch on the shoulder of the astronaut with the gun?)

Reaction, in the Mastodon toot above, was swift to point out that this is an excellent malware vector and data exfiltration channel, since nobody does this kind of deep inspection on DNS traffic on corporate networks.

Counter-reaction, this being Mastodon, was equally swift and informative:

• In the old news file, people mentioned this has been done since the late 80s, sometimes chat programs written by the very engineers who wrote IETF-1035. People have even done voice encoding, for (bad quality) audio calls via DNS. So as security holes go, this is well known and probably blocked?
• Most corporate networks don’t let people query DNS directly, but only to the corporate DNS server that is an internal cache. OTOH, that internal DNS server often just relays queries it doesn’t already know to an outside server, so it might work. In practice, exfiltration of corporate data like this is apparently a famous sales demo used by security vendors.
• “Reasonable” network security (DNS logs, a well built forwarding chain, a properly tuned dashboard, iodine) will detect this sort of mishegoss within seconds. Also, most organizations do not have “reasonable” network security of that sort, even impressively large organizations. (See above using DNS data exfiltration as a sales demo for security vendors.)

The Weekend Conclusion

Computer security is just about impossible. Things can always be suborned into doing stuff they were not designed to do, and in fact are absolutely not supposed to do.

I have no useful advice. Sometimes ya just gotta bear witness to the high weirdness.

(Ceterum censeo, Trump incarceranda est!)

Notes & References

1: Weekend Editor, “DOOM Runs On… What?!”, Some Weekend Reading blog, 2025-Jun-30. ↩

2: A Rice, “Can it Resolve DOOM? Game Engine in 2,000 DNS Records”, Rice’s blog, 2026-Mar-21. ↩

3: Weekend Editor, “DNS: An Improbable Medium for Humor”, Some Weekend Reading blog, 2024-May-02. ↩

The Update from Ukraine

As incorrigibly persistent readers of this Crummy Little Blog That Nobody Reads (CLBTNR) know, we have been expressing… strongly opinions… about Russia’s invasion of Ukraine. ^{[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17]}

The short version: we disapprove.

We’ve been doing some quantitative modeling of the casualty rates (and, at least initially all the other Russian losses). Lately, we’ve been updating every 100,000 (!) Russian deaths. As you can see below, Russia has passed another grim milestone of human sacrifice of their own citizens: 1.3 million dead, in combat operations in Ukraine alone.

We’ve previously defended our use of the Ukrainian Ministry of Defence as a data source; read previous posts for details. Suffice to say: they seem reasonable by comparison with other sources, and I don’t care to argue about it.

Reminder About Russian Demographics

Let’s remind ourselves of the hole being blown in the middle of the Russian demographic of military age males, e.g., about 18-44 years old. Take:

• an estimate of the Russian population,
• divide by 2 to get the men (I’m sure there are Russian women who are soldiers, but I never hear about them),
• then take roughly the middle third as credibly military age, depending on how coercive the Russian government wants to get.

So now our 1.3 million dead is $100\% \times 1.3\ \mbox{million} / 24\ \mbox{million} = 5.42\%$ of the military-age male population, now likely dead in Ukraine.

The Russian emigration and COVID-19 deaths (see older post ^[15]: 900,000 men of military age emigrated and about 67,000 dead of COVID-19), costs about an extra million, for a total loss of 2.3 million. That’s $100\% \times 2.3\ \mbox{million} / 24\ \mbox{million}$, for a total loss about 9.58% of the Russian men of military service age.

That’s getting on towards 10% of the relevant demographic!

These men are gone:

• They will never return to work in the Russian economy.
• Their children will either grow up without fathers or never be born at all.
• Many women in the middle demographic of Russia will face the impossibility of finding husbands.

This is the sort of thing that starts revolutions. (Though Russia is famous for tolerating suffering among its people, for cultural reasons that are inscrutable to me.)

These are truly horrible times.

Our Segmented Regression Model

Our “segmented” regression model is basically a linear model of the number of soldiers killed versus time, except that it can have a kink in it. As we explained previously, this means the number of soldiers looks like:

where:

• $t$ indexes data points in time (here measured in days since 2023-Jan-22; the war itself started earlier, but this is when we started paying quantitative attention),
• $\psi$ is a parameter for estimating the day number at which the kink occurs, and
• $\theta()$ is the Heaviside step function (0 for negative argument, 1 for positive argument, here used as an indicator for “after day number $\psi$”, i.e., the fancy-pants modeling language for an “if” statement),
• $\epsilon \sim N(0, \sigma^2_{\mbox{Soldiers}|\mbox{DayNum}})$ is the error usual error term, normally distributed around 0 with the conditional variance shown.

If we consider expectation values, the interpretation is immediately obvious for the mean number of casualties at a given time:

Here:

• $\beta_1$ is the slope before the kink,
• $\beta_1 + \beta_2$ is the slope after the kink, and
• $\beta_0$ is the slope before the kink & $\beta_0^*$ is the post-kink intercept (depending on the slope difference and the location of the kink in a way about which we generally do not care, for most purposes).

The 2 slopes $\beta_0$ and $\beta_0 + \beta_1$ are the things about which we care most: did the rate of killing Russian soldiers actually go up after the kink?

Here’s what the result looks like, in a plot annotated with lots of delicious statistics:

Statistical Significance & The Need for a Kink

Let’s start with reading the wheat-colored box in the lower right of the plot.

The first item is the Davies test, which tests – essentially – the statistical significance of the difference between before-kink and after-kink slopes. If this gives a large $p$-value, then we realize the true model could be kink-free and what we see is due to chance alone. If this gives a very small $p$-value, then we accept that the kink is worthwhile.

As you can see, $p \sim 10^{-62}$ is absurdly statistically significant: we should very much believe the kink is real, and a necessary part of our model.

At the bottom of the wheat-colored box at the bottom right is a confirmation of this, comparing the errors of the straight line and kinked line models. This is the root-mean-square (RMS) error, measuring how each data point deviates from the fitted model. Note that the RMS error of the kinked model is 3.48 times lower than the simple straight-line model. So we again have evidence that the kinked model does a better job of explaining the data.

The Killing Rates Before & After the Kink

Next consider the middle lines in that wheat-colored box at the bottom right.

These tell us the slopes of the 2 lines, or the killing rates, before and after the kink. Ukraine went from killing about 700/day to killing about 1,200/day. That’s a tremendous increase, percentage-wise:

(Last time, we got around 76%, so this tracks nicely with the previous result.)

We know from the Davies Test that this is statistically significant, but we can confirm it here. Just look at the 95% confidence limits on the slope estimates: they are not just disjoint, but far apart. This means there is almost no chance that the slopes are actually equal, and we just saw them be different by chance.

The Plotted Data

Now we’re ready to look at the plot!

• Axes:
  • The horizontal axis is time, measured in days from 2023-Jan-22 to 2026-Apr-02.
  • The vertical axis is number of Russian soldiers reported killed by the Ukrainian MoD.
• Data points:
  • The blue points in the lower left are the initial training data, 116 days from 2023-Jan-22 to 2023-May-17. They established the initial linear model.
  • The red points in the upper right are more sparsely collected data points from 2024-Apr-10 to 2026-Apr-02. They were collected at approximately every 100,000 increase in casualties (with one exception at 450k).
• Kink position: The vertical gray line indicates where the fitting procedure estimates the kink in the line should be, in this case at 2024-Feb-22. The vertical gray dashed lines on either side indicate the 95% confidence limits, i.e., we’re 95% certain the kink is between 2024-Jan-29 and 2024-Mar-17. (Previously, we’d estimated the kink at 2024-Mar-08, so this is pretty consistent with that.)
• Fitted lines:
  • The black line is the kinked line that we fit, with a kink at 2024-Feb-22. The gray bands around it are the 95% prediction limits, i.e., if you were to use the line to predict a new data point, you’d be 95% certain it would be in the gray band. (I’m not super confident about these confidence limits! The segmented fit seems to be telling me something to which I’m not accustomed; suffice to say the fit is really good.)
  • The dotted line that continues on straight at the kink shows where the original model would have gone, had we not introduced the kink. Obviously, reality is much more lethal to Russian soldiers than the initial model predicted.

The difference between the original straight line (lower left + dotted line continuing past the kink) and the segmented line is visually brutal confirmation that the kinked model is better. This reinforces what we learned above with the Davies test (yes, the kink is likely real) and the reduction in RMS error from 18,000 soldiers to 5,000 soldiers (yes, the kinked model is much closer to the data).

3-Fold Crossvalidation: Is This Real?

The thing that keeps statisticians up at night is worry about overfitting: a more complex model will always fit a bit better, but does it predict better, and is the extra complexity justified?

For example, I could put a kink at every data point. It would perfectly fit any dataset whatsoever, even random data! But… it would be absolute trash at making predictions. The model would be doing little more than memorizing the training data.

That’s why we invented crossvalidation. In this example, we split the dataset into 3 parts called folds, fairly sampling the before-kink and after-kink points in each fold. Then we train the model on 2 of the folds, and measure its prediction qualities on the 3rd fold that it hadn’t seen in training.

If all that looks good (prediction on data subsets never seen during training), then we train one more time on the whole dataset.

This table shows the results of 3-fold crossvalidation (first three rows) and the final training run on the whole dataset (last row).

• The parameters estimated by the model in each fold are the kink position, slope 1, and slope 2. The thing to take away from the table is that they are pretty stable across all 3 folds of crossvalidation: we’re getting a consistent story on all folds.
• The standard deviations of those parameters are also reported, as an estimate of our uncertainty about the estimates. These are also stable, meaning our uncertainty is consistent across all folds.
• Looking at the adjusted $R^2$ for the simple linear model and the kinked model, we see that in all cases the kinked model did better. But, to be fair, not by much: there wasn’t that much room for improvement anyway (most of the data is in the before-kink dataset, and both models get that right).
• The real test of cross validation is the RMS error on the prediction set, the data not seen during training. In all cases, the RMS error of the kinked model is 3-4x lower than the simple linear model.

This means, in essence, the kinked model is performing well on out-of-sample data testing, and is superior to the simple linear model. We should believe the kinked model.

Everything required to peer review the above analysis is available for your inspection. ^[18]

The Weekend Conclusion

Something around 2024-Feb-22, the Ukraine war changed in a way that was much more lethal to Russian soldiers (again, as reported by the Ukrainian MoD). I don’t know what that is. It could be a jump in Ukrainian competence at/commitment to drone warfare, or it could be Russians resorting to human wave attacks, or it could be something else. I’m too lazy to work my way through the word salad of war reporting to try to figure it out; all I can document is that it is real.

It’s hard to explain how angry this makes me. Not just at the stupid cruelty of Russia, but at the lukewarm support Ukraine initially got from the West and now the equally stupid responses of Trump. The most frustrating thing for me, as an American, is that other Americans are not angry enough about Trump, and might blow off voting or acquiesce to ICE brutality and voter suppression. That makes us complicit in many of these evils.

Jack Hardy was one of my favorite folk artists. (“Was”, alas, because he is no longer among us.) He was the éminence grise behind many figures in the New York City folk scene, some of whom under his tutelage became quite famous (e.g., Suzanne Vega).

How do I even begin to ‘explain’ a guy whose trademark was inscrutability? He just knew mountains of literature, poetry, and mythology and sang songs that invited you on a stroll through all of it.

His song “Ask Questions”, in a video of a performance shown here, showcases his breadth of knowledge, allusive & cryptic style where each song is almost a riddle, and of course his famous gravelly voice. You didn’t go listen to Jack for operatic purity, you went to have the boundaries of your mind tugged open a bit.

He died before Trump I, but he knew about our responsibilities when living under an evil system. The relevant chorus:

History has eyes, history has ears.
History finds secrets that are buried for years.
Exploded, explained, exposed, and explicit:
History will judge us either stupid or complicit.
And we know… we are not stupid.
Ask questions.

Don’t be complicit. Don’t be stupid. Break the evil, wring it out of the system and replace it with something better.

Even if Democrats win, complacency will be the major sin toward which they will be tempted. Resist even that.

(Ceterum censeo, Trump incarceranda est!)

Notes & References

1: Weekend Editor, “Another Grim Anniversary”, Some Weekend Reading blog, 2023-Mar-02. ↩

2: Weekend Editor, “Do the Ukrainian Reports of Russian Casualties Make Sense?”, Some Weekend Reading blog, 2023-Apr-15. ↩

3: Weekend Editor, “Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-01. ↩

4: Weekend Editor, “Updated Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-09. ↩

5: Weekend Editor, “Updated${}^3$: Ukrainian Estimates of Russian Casualties Hit 200k”, Some Weekend Reading blog, 2023-May-17. ↩

6: Weekend Editor, “Ukraine Invasion: 250k Russian Dead”, Some Weekend Reading blog, 2023-May-17. ↩

7: Weekend Editor, “Tacitus in Ukraine”, Some Weekend Reading blog, 2023-May-25. ↩

8: Weekend Editor, “Casualties in Ukraine: Grief Piles Higher & Deeper”, Some Weekend Reading blog, 2024-Apr-10. ↩

9: Weekend Editor, “Post-Memorial Day Thought: 500k Russian Dead in Ukraine “, Some Weekend Reading blog, 2024-May-31. ↩

10: Weekend Editor, “Ukraine: 600k Russian Dead”, Some Weekend Reading blog, 2024-Aug-27. ↩

11: Weekend Editor, “Ukraine War: 700k Russian Dead”, Some Weekend Reading blog, 2024-Nov-04. ↩

12: Weekend Editor, “Ukraine War: 800k Russian Dead”, Some Weekend Reading blog, 2025-Jan-08. ↩

13: Weekend Editor, “Ukraine War: 900k Russian Dead”, Some Weekend Reading blog, 2025-Mar-21. ↩

14: Weekend Editor, “Ukraine War: 1,000,000 Russian Dead?!”, Some Weekend Reading blog, 2025-Jun-12. ↩

15: Weekend Editor, “Ukraine War: 1,100,000 Russian Dead”, Some Weekend Reading blog, 2025-Sep-22. ↩

16: Weekend Editor, “Ukraine War: 1,200,000 Russian Dead”, Some Weekend Reading blog, 2025-Dec-31. ↩

17: Weekend Editor, “Ukraine War Casualties: A Segmented Regression Model”, Some Weekend Reading blog, 2026-Jan-28. ↩

18: Weekend Editor, “Updated R script for analysis of Russian Casualties in Ukraine”, Some Weekend Reading blog, 2026-Apr-02.

The data driving the original analysis, in .tsv format, is also available for review by the persistent skeptic.

The data driving this analysis, in .tsv format, is also available for review.

There is also a transcript of running the script, for your review.

This whole mess depends on some idiosyncratic subroutine libraries of our own construction, graphics-tools and pipeline-tools. We are happy to supply these to our most exceptionally persistent skeptics who wish to reproduce these results. :-) ↩

Jack Hardy: “Ask Questions”

Jack Hardy was (alas, past tense) a force with which to reckon on the New York City folk scene.

His voice was gravelly, nothing special (as you can hear below). But if you listened to him… oh, good heavens! You’d find he was deeply literate in Irish poets, Celtic mythology, and the bardic tradition. The songs were magical, sometimes in the literal sense that folks who practice “magick” would recognize the invocation of a spirit of understanding, peace, and knowledge.

He was a mentor to other artists, raising many of his fellows up to fame. If you follow American folk music, you probably know some their names: Suzanne Vega, John Gorka, Shawn Colvin, Lucy Kaplansky, Christine Lavin, Richard Shindell, and David Massengill. He was famous for having weekly spaghetti dinners in his Greenwich Village apartment where they’d all present a song and listen to the critique of the others. So he gave a lot to the community, making stars of some of them, even though his own popularity never quite reached that level.

He performed reasonably frequently in Cambridge, and I almost always managed to be there. He usually performed in a dramatic black velvet jacket. Sometimes he couldn’t decide if he was a singer or a comedian, given the elaborately funny and deep introductions.

He usually looked like this album cover of The Hunter, giving you the side-eye with a little grin that made you think he knew something you didn’t know. And… he almost always did know something you didn’t know, and was about to spring it on you as a joke.

The song “The Hunter” on this album was practically my personal theme song through the 1980s. If you asked Jack what it was about, you’d get that side-eyed grin and hear it took place in a coffeehouse in Greenwich Village about 7,000 years ago. (Saw it happen, with my very own eyes and ears. Not just once, but a couple of times. More questions almost never helped.) After all, there aren’t many songs about magic, astronomy & how the constellations move with the precession of the earth’s spin axis over 26,000 year periods, deep history, the myth of the year king, the bardic tradition, and the tension felt by herders about the invention of agriculture. At least, that’s what I could glean from Bullfinch’s Mythology and Frazer’s Golden Bough. (And now you know a little bit about my misspent youth. For all I know, the song took place in a coffeehouse in Greenwich Village about 7,000 years ago.)

His political point of view was seldom discussed, more from it being obvious than anything else. It probably helped that I was in vehement agreement most of the time: it’s important not to give power to the barbarians!

Two of his political songs about come to mind, shown here:

• “Worst President Ever” does’t actually name George W Bush, but it was archly implied by lyrics admiring other political sarcasm that didn’t need to name the target.
• “I Ought to Know” is a song Jack used to swear up and down was not about W, but from my point of view it might as well have been. It’s about the sneering and proud ignorance paraded on the right, who think that because they’re conservatives they are somehow exempt from knowing much of anything about where & when they are, and how the world works.

Those are both strong candidates.

But for Trump, we need something special for the special boy. We also need something that lays responsibility for his removal, trial, and (one may hope) conviction squarely upon our own backs.

Thus, the song “Ask Questions”.

It’s about our duty to ask questions about policy, especially the questions leaders find inconvenient. It’s about our duty to rear up on our hind legs and act like responsible human adults, daring to hold our leaders accountable.

Pay particular attention to the chorus:

[Verse 1]
The dust bowl is flooded, the northwest is dry
Someone strike a match to shed us some light
But all that is burned is a cross in the yard
And a flood in the Ninth Parish Ward

[Refrain]
Climb up the hill to the Capitol
Dare to hold them accountable
Ask questions

[Verse 2]
And Jefferson the patriot, fearless and bold
Takes Sally Hemmings when she’s fourteen year old
Cannot resist, cannot deny
The way his descendants now have to try

[Refrain]
Climb up the hill to the Capitol
Dare to hold them accountable
Ask questions

[Chorus]
And history has eyes, history has ears
History finds secrets that are buried for years
Exploded, explained, exposed and explicit
History will judge us either stupid or complicit
And we know we are not stupid
Ask questions

[Verse 3]
Remember the Maine, Lusitania too
The Gulf of Tonkin and Pearl Harbor too
Where there’s a will there’s a way to go to war
And a profit without honor no more

[Refrain]
Climb up the hill to the Capitol
Dare to hold them accountable
Ask questions

[Verse 4]
And Joshua believes in heaven and in hell
Polishes his trumpet in a desert motel
Gamblin’ and whorin’ ‘til his time comes around
And the towers come tumblin’ down

[Refrain]
Climb up the hill to the Capitol
Dare to hold them accountable
Ask questions

[Chorus]
And history has eyes, history has ears
History finds secrets that are buried for years
Exploded, explained, exposed and explicit
History will judge us either stupid or complicit
And we know we are not stupid
Ask questions

The Weekend Conclusion

“History will judge us either stupid or complicit – and we know we are not stupid.”

(Ceterum censeo, Trump incarceranda est!)

Notes & References

Yes, I haven’t blogged in a bit. Mea maxima culpa! Here are a few items all glommed together into one post.

The Twelfth Vaccination

Yesterday I got my 12th COVID-19 vaccination (though not by the Twelfth Doctor).

Now I can hear some of you whining already: “Twelve?! Isn’t that a lot?” No, it is not a lot. It is, in fact, exactly the right number:

• In spring 2021: the initial shot & booster followed by a booster in the fall. So that’s 3 vaxes for 2021.
• In years 2022-2025: 2 boosters, separated by 6 months, as recommended for those over age 65. So that’s 2/year times 4 years = 8 vaxes.
• And now the first booster of 2026.

And all that adds up to 12, exactly the right number to comply faithfully with medical guidance for seniors. You should consider following that advice too. (Or the once a year version if you’re under 65, in which case the correct number now is 7 or 8, depending on what you did in 2021.)

It’s just like the flu vaccine: the virus changes annually, and broad immunity fades over time, so you get an annual flu shot. (You do get an annual flu shot, don’t you?)

In our exercise class – consisting mostly of middle aged Japanese women and me, the gaijin/yabanjin outlier – people were asking, “Do we really still have to do that?!” Yes, we really still have to do that. Every infection causes cumulative damage for the rest of your life.

The vaccination sequelae were pretty tame this time. Last fall, I had one moderately annoying night after mNEXSPIKE. But this time, not so much. Nothing much in the way of measurable fever, just tired and achy for a day or so (more than usual, anyway). Well worth it. Kind of disappointing, really: I was hoping for a strong innate immune reaction. Maybe my body’s seen this vaccine before and knows not to over-react, or maybe I’m just old now.

Either way, I’ve done my part to keep myself safe and to keep those around me safe.

The next project is persuading the Weekend Editrix to take her turn.

Now, on to other madness!

BlueSky Clustering

Somebody has decided to apply statistical cluster analysis to 3,137,131 social media accounts on BlueSky. The details on exactly what they did is pretty scant, but my guess is:

• Map each account to a frequency vector in the space of the union of words found in all of them.

  Typically, one would use a stopword list to avoid counting words that are more about syntax and less about meaning, like “the” in English.

• Then use dimensional reduction to 2 or so dimensions. (It looks like they then just made a plot, and looked for lumps.)

  The classic way would be multidimensional scaling, which I’ve used in the past to some good effect. Nowadays I’d prefer some kind of principal components method like SVD.

  It looks, just from the plot, that they used tSNE, which all the cool kids are doing nowadays. Yes, it’s popular, but I hate it. I once had a postdoc who wanted to understand how this works, so I had her generate some random data and then use tSNE. Of course, it found clusters: every single one was a false positive! (Verified by kernel density estimation in the original higher-dimension space.) While I don’t mind tSNE as a visualization of clusters obtained in a more respectable way, but it’s terrible practice just to look at the plot and say, “Ooh, what’s this lump here?”

• Then you’d like to cluster those vectors somehow, grouping those that are near in some metric you find interesting. I favor $k$-means with a variety of distance metrics, but there are many alternatives.

  It looks like they didn’t do that. Instead, they just did visual bump-hunting on the plot, sampled a few points in each bump, and took a guess at what to call it.

Ok, I’d have done it differently. But… they actually did it, whereas I did not! So let’s give them credit for action, and see what kind of results they dug up.

Here’s what 3,137,131 BlueSky accounts look like as of today, reduced to 2 dimensions. You can definitely see lumps in it (though if this is tSNE I’m suspicious). Looks sorta like colliding galaxies, doesn’t it?

If you click through to embiggen the image, you’ll see the BlueSky account for this Crummy Little Blog That Nobody Reads (CLBTNR) is labeled in purple in the mid-lower left. It’s part of a large “cluster” labeled the Resistance Plateau. (They use geographic and map features as names.) And that’s fair enough: for all the venom I have against Republicans in general, and Trump in particular, “resistance” is not a bad description.

If you go to their site and zoom in, you’ll find this CLBTNR’s BlueSky account is next to other groups, much more sketchy in their cluster boundaries, labeled:

• Democracy Journalism Network,
• Public Interest Media Corridor,
• Legal Scholar Faculty,
• Boston Media Hub,
• Tech Policy Forum,
• Accountability Journalism Ridge,
• Progressive Journalism Corridor, and
• American Political Journalism Corridor.

While I’m being a cranky old statistician about the lack of equations describing their methods and the more or less heuristic way clusters appear to be labeled… that’s not a terribly bad description of the company I keep.

Of course, it misses out on a lot of the math and statistics stuff I do here. So maybe I need to do more of that, and write about it on BlueSky. (See, I drew a useful conclusion from their data already!).

Donald Trump Meets 16th Century Polyphony

From Siderea at Sibylla Bostoniensis comes some interesting musical and political news.

Jonasquin at YouTube has written and performed a motet, shown here, in the style of Josquin Desprez (~1450 – 1521) based on Ps 10:2,3,7-11 with a minor flourish at the end applying it all to Donald Trump. (You might have to click through to YouTube to see it. They’ve been getting regrettably anal about sign-in for embedded videos on CLBTNR’s like this.) If you listen carefully, when the singing heads show up at the top of the video, you might find a message which is as applicable as it is extra-canonical.

Siderea’s summary: “Dum superbit imperius”. This is a phrase from the Vulgate Ps 9:23 (note Vulgate verse numbering is not exactly the same as modern versions, so you may have to hunt): “Dum superbit impius, incenditur pauper”. The approximate Weekend Translation is “While the wicked are proud, the poor are set afire.” Which is… regrettably apt for the world situation, and particularly lamentably apt for the US.

Line labels in the English (except the last line) translation below are timecodes into the video:

0:00 In his arrogance the wicked man hunts down the weak  
0:43   who are caught in the schemes he thinks up.  
1:12 For the sinner boasts of the desires of his soul  
1:33   and the wicked blesses himself.  
1:47 His mouth is full of foul language and bitterness and deceit,  
2:10   under his tongue are mischief and pain.  
2:49 He sits waiting to ambush with his wealth in secret  
3:03   to murder the innocent.  
3:32 His eyes watch in secret for the poor,  
3:41   he lurks in cover, like a lion in his thicket.  
4:02 He lurks to catch the poor,  
4:10   to catch the poor and drag him in his net.  
4:32 Trapped, the victim is crushed and collapses  
4:49   as soon as he has him in his might.  
5:07 For he says to himself:  
5:13 "God has forgotten,  
5:20   he turns away his face so that he never will see."  
5:32 Donald Trump est in Epstein documentis.  

Codex Epsteiniana divulganda est, indeed!

A Clever Way to Get Past Mines in the Strait of Hormuz

Speaking of the evils of Republicans, Trump has (of course) started a war in the Middle East. (NB: If you were born after about 1980, then every Republican president in your lifetime has crashed the economy into recession and started a war. Learn from the pattern!)

This time, Iran has ‘closed’ the Strait of Hormuz, choking off a large portion of the world’s oil supply. Interestingly, this also chokes off about 1/3 of the world’s helium supply. Helium is essential for supercooling equipment used in chip making, the pressurized gas inside hard disks, and super-cooling medical instruments like MRI machines. So if later this year you can’t get an MRI required, say, to set a broken bone… just remember: Trump Did That.

So everybody’s interested in the problem of how to get shipping, especially tankers, past probable mines. Here’s a picture from a somewhat unrelated, but equally stupid, New York Times article showing an optical illusion of a tanker flying over the top of the sea. (Basically there’s a trick with sea & sky color matching, and light being bent in humid air.)

It would be nice if one could fly a tanker over the mines. Although, if one could fly a tanker, why not fly it overland and avoid the Strait altogether? And what’s the theory for avoiding drones, missiles, ‘mosquito fleets’, and so on?

Oh, right: as an illusion, this is somewhat reality-impaired… not actually existing, as such.

The world is so awful, and so driven by deeply evil people, that even an illusion is comforting.

On Reading Old Books

Meanwhile… on BlueSky, a report on the barbarians and their attitudes on books:

Really?! Nothing more than 50 years old can penetrate her skull?

Sometimes the stupidity is so venomous and the ignorance is flaunted with such concentrated pride that… well, one barely knows where to start.

I mean, you can take it as read that since I’m a member of a religious community, we are always reading texts that are centuries to multiple millennia old, and interpreting them in ways to maximize compassion and caring. Just a couple weeks ago, I was in a conversation where the phrase “I hope all is well enough” sparked memories of:

• Carl Rogers, the humanistic psychologist. He embraced the fact that he was not perfect, and not a total solution for his patients. But enough for now. From On Becoming a Person (1961), or maybe from Client-Centered Therapy (1951) (I forget which was the source in my quotes file, but both are more than 50 years old):

  Before every session, I take a moment to remember my humanity. There is no experience that this man has that I cannot share with him, no fear that I cannot understand, no suffering that I cannot care about, because I too am human.

  No matter how deep his wound, he does not need to be ashamed in front of me. I too am vulnerable. And because of this, I am enough. Whatever his story, he no longer needs to be alone with it. This is what will allow his healing to begin.

• Julian of Norwich, a famous 14th century English mystic (using “famous” in the broadest possible sense): “All shall be well, and all shall be well, and all manner of thing shall be well”.

  To give you a sense of how radically optimistic that was, she was both an anchorite (locked up in a cell by her own choice), and writing during the Black Death. Her theological position was not to deny the reality of pain, but to deny that it could be the last word. For her, divine mercy & divine love were the last word on human existence.

Or never mind the relevance to the BS firehoses of modern AI in the old oracle myths. The oracles are always ambiguous, you’ll always misinterpret, it will always go badly, and it will always be your fault. “Just check the AI answers” is not instruction; it’s a threat of legal liability: the AI is permitted to be wrong, but you are only permitted to be responsible. The Ibis/Redibis story of the oracle at Dodona is frightening enough that it’s occasionally used in law schools to illustrate the crucial nature of clear writing (and punctuation, in this case).

Or never mind Dante’s Purgatorio, one of the best books on repentance and taking a bend toward the light that I’ve ever read. (Though, admittedly, you have to get past the pain metaphors of a 14th century European Catholic!)

I suddenly have a theory: maybe the OP thinks Shakespeare’s Tempest was cribbed from Forbidden Planet, and has no idea how funny that is? (Obviously, it was some of Leslie Nielsen’s earliest comedic work…)

Some wag (tell me if it was you, so I can cite you!) showed me this 4-way Venn diagram of dystopian novels, describing the current day as the intersection of all the bad ideas we’ve resurrected from our past. Maybe if we’d read some of these books, we could take the counterexamples to heart?

Also, as a card-carrying data analysis nerd, I have to point out the Venn diagram is done wrong. It shows only 13 non-empty intersections, whereas for 4 sets there are $2^4 - 1 = 15$ non-empty intersections. An example is shown here, for inspiration.

Anybody want to add a couple more dystopian novels? Nevil Shute’s On the Beach and Goethe’s The Sorrows of Young Werther, maybe? I’m pretty sure Trump would like the obvious starring role in the first book of Milton’s Paradise Lost, no?

So instead of the bizarre dismissal of anything insufficiently “modern”, I commend to you the advice of Niccolò Machiavelli, in a letter to his friend Francesco Vettori, 1513-Dec-10 describing his life in exile:

On the coming of evening, I return to my house and enter my study; and at the door I take off the day’s clothing, covered with mud and dust, and put on garments regal and courtly; and reclothed appropriately, I enter the ancient courts of ancient men, where, received by them with affection, I feed on that food which only is mine and which I was born for, where I am not ashamed to speak with them and to ask them the reason for their actions; and they in their kindness answer me; and for four hours of time I do not feel boredom, I forget every trouble, I do not dread poverty, I am not frightened by death; entirely I give myself over to them.

A friend once bemoaned the fact that his students at university cared nothing for history or literature, had no idea when they were in time, or whether their era was the best (it was not). He said we’re not turning out educated adults, we’re turning out “skilled barbarians”.

Oh, and I Also Just Voted

As long as we’re speaking of barbarians, it’s important to keep our voting registration in order so we can turn out the current crop of Fans of Tamburlaine The Great (another regrettably relevant bit of old literature).

So I just did my part, voting in a purely local election (though those are important in their own way, too). I voted by mail, and a couple days later checked with the office of the secretary of state. As you can see here, my ballot was received, validated, and accepted for counting.

It’s important to vote every time you can, keeping your registration current to avoid the inevitable shenanigans of voter suppression this fall!

The Weekend Conclusion

We live in dark times. Humor is essential, especially derisive humor directed at the fascist lesions on the body politic.

Alas, the American media is largely useless, mired in both-sides-ing, or outright capitulation to the régime. European media is, sometimes, a bit better. Here is the French cartoonist Guffo, in Le Monde, reminding us a few evil people are the source of a lot of our woes. Yes, we have systemic problems that will have to be fixed once we rid ourselves of the current problem, but those causing the current problems are painful.

Seeing the signature Trump tie hanging out of the Epstein files reminds us: Codex Epsteiniana divulganda est!

As always: Ceterum censeo, Trump incarceranda est.

Notes & References

Nope.

They Did What?!

Remember Moderna? The company that made one of the mRNA vaccines for COVID-19?

They’ve had a robust research program numerous clinical development programs for things other than just COVID-19: several cancer vaccines, some disease vaccines, and in particular a flu vaccine.

• Their flu vaccine trial involved 40,000 people, starting 2024-Sept.
• The trial design was previously accepted by the FDA, and by the medical regulatory authorities in every other nation on the planet where it was simultaneously submitted. (That appears to include at least the European Union, Australia, and Canada.)
• It seems to be at least somewhat superior to existing flu vaccines in people over age 50. It was, in fact, 27% more effective vs symptomatic flu, and 49% more effective vs hospitalization.

That “demonstration of non-inferiority to standard of care” is the gold standard: you compare against how we’d usually treat a disease, and see if you can do better. Trials like this are designed in conjunction with the FDA, who usually give a couple of years of advice on how to do it the way that’s best for them. It’s never a surprise to the FDA when you submit a clinical trial result, since they helped you design it in the first place.

So it was with some alarm today that the FDA has refused even to consider the submission of the Moderna flu vaccine trial results, via an AP article. ^[1] That was sufficiently alarming to be worth checking to make sure other outlets in and out of the US news bubble agreed, so here are some pointers to The Guardian ^[2] and the “ol’ reliables” at STAT News, Matthew Herper and Helen Branswell. ^[3]

So, ok. I’m satisfied this is real news. It is, however, extremely unusual!

I have never seen a “refusal to review” letter when the agency had previously approved the trial. Apparently the objection is, in the words of FDA vaccine director Vinay Prasad, that the trial was not an “adequate and well-controlled trial” because the standard of comparison wasn’t the FDA’s preferred flu vaccine. This is also extremely unusual, since that was hashed out a couple years ago and the FDA agreed that the control vaccine used in the trial was ok and gave it the green light.

The consequences will be absolutely damning, going beyond medical risk to research risk in not pursuing vaccines in the future. As The Guardian put it:

“This is likely to discourage industry from investing in future influenza vaccines, and makes working with the US FDA uncertain and problematic,” said Dorit Reiss, professor of law at UC Law San Francisco.

“They are refusing to review a new vaccine with a more flexible technology, while creating a real risk we will not have traditional vaccines for next year.”

Future vaccine innovation will almost immediately move overseas.

Moderna has just announced exactly that, additionally killing projects because the US no longer makes it possible to break even on their current vaccine candidates for Epstein-Barr virus, herpes simplex virus, and shingles virus. These cures are now lost to humanity; even when governments change it may take generations to rebuild the capacity now being destroyed:

And, of course, infectious diseases are not the only things being lost. There are some very good cancer vaccines in the pipeline; in fact, immuno-oncology was perhaps the most promising area when I retired from oncology in 2020. Some of the results are startlingly good:

… but, apparently no more. It seems Moloch demands even more lives be sacrificed, with Republicans salivating to trade more lives for short-term power in their base.

It appears ^[4] that the FDA scientists were fine with Moderna’s trial, but were overruled personally by Trump/Kennedy protégé Vinay Prasad, who is currently the controversial head of the FDA Center for Biologics Evaluation and Research (CBER). The Wikipedia page on Prasad, linked here, notes that Prasad tends to push emotional hot buttons and some of his writing has amounted to fearmongering.

So… it’s personal with Trump/RFKJr/Prasad, now.

The Reaction

Reaction among scientists has been swift and relentlessly negative, as you might expect.

And it’s not just me: here’s an article from renowned med-chem writer Derek Lowe, a man normally of somewhat conservative/libertarian leanings, who over the last few years has become as enraged against Republicans as your humble Weekend Editor. ^[5]

Last night brought news that the FDA has refused to review Moderna’s application for their new mRNA influenza vaccine, and more details have emerged so far today. All of them are infuriating.

Like me, he sees this as extremely unusual, rising to “unheard-of” territory:

Right off, let’s just make clear that an outright refusal-to-review rejection like this is quite unusual, since biopharma companies (large and small) typically work with the FDA during their trials to make sure that things are being run in a way that the agency finds acceptable. Why wouldn’t you?
…
It is especially unusual for a vaccine. If there is a prior example like this with the FDA, I am unaware of it. Moderna seems baffled by the decision in their public statements, and I can’t blame them.

And it really does seem to be some personal jihad down to Prasad:

It appears that the agency - well, Vinay Prasad - told the company that they did not run an adequate trial … Prasad signed the rejection letter personally, which is also something I’ve never heard of before, so draw your own conclusions.

The controls used by Moderna were absolutely reasonable, and even though the FDA a couple years ago had some suggestions, they signed off on these controls (GSK’s Fluarix quadrivalent vaccine for adults 50 or older).

Derek reaches about the same conclusions as me (emphasis added):

And let’s get real here: this application is being denied, personally by Vinay Prasad and against the recommendation of the FDA’s remaining experts, because he and the rest of the Trump administration are hostile to vaccines in general and to mRNA technology in particular. I don’t see how anyone can look at the statements and actions of the political appointees (from RFK Jr. on down) and come away with any other impression. We are deliberately walking away from the most advanced form of one of the most effective public health measures available to the human race…

Like so many of the Trump administration’s actions, this is simultaneously weird, dangerous, and profoundly stupid. And we are all going to pay the price for it.

Now, I can already hear the objection that this is just the opinion of some weird, hippy scientists, and who cares what the longhairs think? (Let the record show that my hair is considerably longer than Derek’s.)

How about The Wall Street Journal? Is that sufficiently anti-hippy to pass your conservative purity tests? Because the WSJ coverage ^[6] points the finger of blame directly at Prasad, and is subtitled, “Does the White House know the harm he’s doing to public health?”

It doesn’t let up, either, with this opening paragraph:

It’s hard to recall a regulator who has done as much damage to medical innovation in as little time as Vinay Prasad. In his latest drive-by shooting, the leader of the Food and Drug Administration’s vaccine division rejected Moderna’s mRNA flu vaccine without even a cursory review. This is arbitrary government at its worst.

They report that Prasad wanted Moderna to have used a high-dose flu vaccine in the control arm. This is not even possible:

• In the US, those are only for seniors over 65. This trial was about people over 50, for whom the high-dose vaccines would have been medically inappropriate.
• The high-dose vaccines are not even available in Europe, where the trial was largely conducted.

So Prasad demands a medically inappropriate & not legally available control vaccine, thereby making it impossible for the trial to be conducted.

But Of Course, We’ll Always Have… Ivermectin?!

Instead, we are apparently funding a trial of ivermectin in cancer, of all things. ^[7]

Lots of things kill cancer. Usually they do so at doses that kill normal tissue, too. Normal scientists know this. Trump/RFKJr/Prasad apparently do not, or are willing to pretend not to know it.

This is pure political appeasement to the Trump base, who have a superstitious attachment to ivermectin. Incorrigibly persistent readers of this Crummy Little Blog That Nobody Reads (CLBTNR) will recall that, in the past, we’ve had vehemently negative things to say about the right-wing superstitions around ivermectin. ^{[8] [9] [10] [11] [12]}

Let’s be clear about a few things:

• Ivermectin is a perfectly reasonable drug for treating worm infestations, lice, and other invertebrate parasites.

  If you’ve got worms, this might be the drug for you. In the US, worms in humans are rare but it’s widely used for veterinary purposes, hence the name “horse paste”.

• Ivermectin does not treat COVID-19, and never has.

  The hints otherwise came from clinical trials conducted in countries where worm infestations were common. Worm infestations make everything worse. So if you have worms and COVID-19, ivermectin will help a little. (But what you really need in that case is ivermectin and paxlovid, because you have 2 separate problems.)

• Ivermectin is a “virtue signal” extremely strongly associated with right-wing disinformation.

  It’s so hard to get people to let go of ivermectin because they don’t want to lose their entire tribal identity as Trumpers or Republicans. It’s difficult to admit you’ve been conned!

But… now apparently the knuckleheads want to test ivermectin in cancer. The linked article points out that there is no evidence that ivermectin treats cancer. You will, of course, be unsurprised to hear that the new head of the National Cancer Institute (NCI) is a Trumper.

You do not want to be in this clinical trial! The “treatment” arm is a nonsensical application of a de-worming drug, so your best bet would be to get in the control arm, where you’d get standard of care. Though… given Prasad’s fixation on placebos, maybe you’d get no treatment at all – in violation of every medical ethis code.

Internal NCI scientists have reacted about as you might think:

The decision by the world’s premier cancer research institute to study ivermectin as a cancer treatment has alarmed career scientists at the agency.

“I am shocked and appalled,” one NCI scientist said. “We are moving funds away from so much promising research in order to do a preclinical study based on nonscientific ideas. It’s absurd.”

Absurd.

And for that absurdity, we kill mRNA vaccines for infectious diseases and cancer.

The Weekend Conclusion

The rest of the world looks askance at the utter clownshod goings-on in the US. Here, for example, is a visualization from Visual Capitalist ^[13] of the relative rankings of countries by reputations, and how they changed from 2024 to 2025, i.e., after the advent of Trump.

• A couple oddities: Cuba & Venezuela are in the list on the left, but disappear. Instead, Taiwan and Kuwait suddenly appear on the right. Hmmm.

• The US in recent years has never been terribly highly ranked abroad. We are too violent, too impulsive, too superstitious, and too prone to demagoguery.

  Hence, on the left hand side, you see the US in about the middle at rank 30, between Brazil and Ukraine. So we’re not starting from a very reputable place.

• With the (re-)advent of Trump, our reputation abroad has plunged!

  We are now at position 48, between Kuwait and Kazakhstan.

  This is how the rest of the world sees us. Trump in particular, and Republicans in general, are not brave visionaries. They are incompetent, dangerous, and fascist.

We are ruled by ignorant children. Their understanding of science just superstition. Their every other thought is about acquiring & keeping power, regardless of who might be hurt. In this case, their performative fear of mRNA vaccines is an attempt to cement power in their superstitious base.

By forbidding a potentially superior vaccine while offering the most ignorant of excuses, they set up a situation where people will die. But if it’s in the service of Republican power, they probably think that’s acceptable. Moloch demands no less.

(Ceterum censeo, Trump incarcerandam esse.)

Addendum 2026-Feb-18: FDA Changes Its ‘Mind’

It appears the outcry of despair and contempt from the scientific & medical communities has caused the FDA to change what’s left of its mind. ^[14]

• They will review the vaccine for adults ages 50-64 under normal rules.
• They will review it for seniors over 65 under accelerated approval rules, but will require a post-marketing study.
• However, they will “aim to review the vaccine by Aug. 5”, which is almost certainly too late for the vaccine to get into the pipeline for this fall’s flu season.

The requirement for something like Phase IV on a flu vaccine is a very odd extra requirement, it seems to me. And I just don’t get the foot-dragging on approval until it’s more or less too late. Maybe it takes time for them to make up disinformation to throw at it?

The FDA said Moderna didn’t follow their advice to use the high-dose vaccine in controls, but:

1. The FDA previously said the control vaccine used was acceptable, so Moderna did follow their revised advice. Pretending otherwise is just Prasad lying about it, signaling that FDA instructions can be changed without notice or rationale.
2. The high-dose vaccine is not medically appropriate for the participants ages 50-64.
3. The high-dose vaccine is not even legally available in Europe, where much of the trial happened.

So they’re sticking to just outright lying about what is happening, and demanding a fantasy of medically inappropriate and outright illegal controls. In a particularly venomous moment, the recently appointed Marty Makary flirted with what looks to this non-lawyer like libel, by calling the Moderna trial “unethical”.

But… they changed their minds, or somebody overrode Prasad, or….

Now at least the mRNA flu vaccine will be reviewed. On the other hand, it’ll be too late for this year’s flu season, the anti-vax nuts will almost certainly try to prevent approval, and Trump/RFKJr/Prasad/Makary are still campaigning against science.

Notes & References

1: L Neergaard & M Perrone, “Moderna says FDA refuses its application for new mRNA flu vaccine”, Associated Press, 2026-Feb-10. ↩

2: M Schreiber, “FDA declines to review Moderna application for new flu vaccine”, Guardian, 2026-Feb-10. ↩

3: M Herper & H Branswell, “FDA refuses to review Moderna’s influenza vaccine”, STAT News, 2026-Feb-10. ↩

4: L Lawrence, “Prasad overruled FDA staff to reject Moderna’s flu vaccine application”, STAT News, 2026-Feb-11. ↩

5: D Lowe, “An mRNA Refusal to File”, In the Pipeline blog at Science, 2026-Feb-11. ↩

6: WSJ Editorial Board, “Vinay Prasad’s Vaccine Kill Shot”, Wall St Journal, 2026-Feb-11.

NB: Regrettably paywalled; see archive copy here. ↩

7: R Pradhan, “National Cancer Institute studying ivermectin’s ‘ability to kill cancer cells,’ alarming career scientists”, STAT News, 2026-Feb-10. ↩

8: Weekend Editor, “Three Lessons from COVID”, Some Weekend Reading blog, 2021-Nov-08. ↩

9: Weekend Editor, “A Couple Ivermectin Takedowns”, Some Weekend Reading blog, 2021-Nov-19 ↩

10: Weekend Editor, “Ivermectin Revenant”, Some Weekend Reading blog, 2022-Mar-07. ↩

11: Weekend Editor, “Ivermectin vs Strongyloidiasis Paper Published”, Some Weekend Reading blog, 2022-Apr-18. ↩

12: Weekend Editor, “Missouri: Ivermectin Gag Order”, Some Weekend Reading blog, 2022-May-20. ↩

13: M Lu, “Ranked: Countries With the Best Reputations in 2025”, Visual Capitalist, 2025-Oct-06. ↩

14: L Lawerence, “FDA reverses course, agrees to review Moderna’s flu vaccine”, STAT News, 2026-Feb-18.

NB: Archive reference, unpaywalled. ↩

If the World Sells US Treasuries…

US Treasury bonds, and their inflation-protected cousins, TIPS, were widely regarded as the safest investments in the world. However, the US is behaving so badly, many foreign holders of our debt have begun thinking what was previously unthinkable: selling off their stocks of Treasuries. Mostly that’s been just talk in the past. After all, taking down the US debt market would likely cause a world-wide Depression that nobody wants. But the US now such a menace to itself and others, that seems like the reasonable move!

Two recent articles show some ominous cracks in the dam.

A small-ish Danish pension fund, AkademikerPension, says it’s going to dump \$100 million in US bonds by February, i.e., now. ^[1] Now, true, that’s not much compared to the size of the debt market. But considering how conservative European pension funds are, and how unthinkable this would have been just a year ago, it’s a very significant early warning.

Not at all coincidentally, the Swedish pension fund Alecta says it has already sold of almost all of its Treasuries, amounting to \$7.7 – \$8.8 billion. ^[2] Again, that’s not a huge amount, but the first signs of huge moves are always small.

Yes, this is an early reaction from a couple of pension funds which, after all, are rather small. But that’s how an avalanche starts: first just a small bit, then all at once. So we want to have in place measures which are (a) defensive against a decline in US Treasuries & TIPS, and (b) not too destructive to overall return.

How Can We Defend Against That?

Not defending Trump, of course: he deserves all he can get in terms of world leaders metaphorically slapping him around. Rather, how can we defend our portfolio which relies heavily on US Treasuries & TIPS for its bond sector?

This is a bit like asking how individuals can defend their homes in case of nuclear war. A US debt collapse would be so disastrous that we can’t really do much at all. Still, perhaps we can do something to hold off the damage in case there’s a reaction against the US debt that is very bad in itself, but not a total collapse. As we’ve written previously on this Crummy Little Blog That Nobody Reads (CLBTNR) ^{[3] [4] [5] [6] [7]}, our neutral policy portfolio would be a bog-standard set of index funds, spread all around the world, at a 60% stocks and 40% bonds ratio, using US Treasuries & TIPS as the bond portion.

In a series of steps, encouraged by public advice from Vanguard, we had moved to a 40/60 allocation:

• 40% stocks / 60% bonds
• 40% US / 60% international in stocks and REITS

But within the stock sector, we remained 60% capitalization-weighted total market index funds to 40% “tilts” to small-cap and small-cap value funds. Those tilts importantly both capture the Fama-French model premia, and tilt us away from US large-cap big-tech AI bets, which look like sheer lunacy to me.

Also, just because we’re a bit conservative, we remained 50% US Treasury & TIPS / 50% international bonds. The Vanguard International Bond Index fund (VTABX) is intriguing: it’s mostly government bonds of developed nations, and has a currency hedge back to the dollar to eliminate currency risk. So it looks pretty much like Treasuries, just someone else’s Treasury backing it up.

It’s that last bit that we want to address now, before any hostility to Treasuries builds up.

In response to the world-wide, and generally well deserved, hostility to US Treasuries, we decided to move the bond sector of our portfolio to 40% US Treasuries & TIPS / 60% international dollar-hedged bonds.

• As you can see here in the first couple pie charts, our overall tax location and asset allocation haven’t changed much.

  We’re still investing in the same broad asset classes in about the same way, with continuing effort to Roth convert funds to be more tax-free in the future.

• The changes come when you look at the bond portion of the allocation in the next table (the lines with the orange cells, labeled “Bonds”).

  Here we’ve cut back to smaller allocations to intermediate Treasuries & TIPS, and expanded the foreign bonds.

• Just to be sure, I got another opinion by using Vanguard’s portfolio tools to get a snapshot of the resulting allocation. I might be wrong about the future, but I don’t want to blunder in how I prepare for it!

  Vanguard’s tool confirms that we’ve done approximately what we intended, and that our expense ratio is a comfortingly low 10bp.

So now our portfolio is even more armor-plated against world hostility to Treasuries. We’re probably sacrificing some return. That’s acceptable, a bit like paying an insurance premium to off-load a risk. As Vanguard claimed in their advice, the 40/60 portfolio should have almost exactly the same return over the next 10 years as the 60/40 portfolio, but with dramatically less risk.

We now stand at:

• 40% stocks / 60% bonds
• 40% US / 60% international in stocks, REITs, and now also in bonds
• 60% cap-weighted total market index funds / 40% tilts to small and small-value index funds, within the stock sector.

The Weekend Conclusion

Keep in mind, this is not investment advice. I’m (a) unaware of your particular situation, and (b) neither competent, licensed, nor inclined to give investment advice.

It’s just a description of what we’re doing to cope with retirement.

Caveat investor.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: M Katz, “Danish Pension to Sell Off All US Bonds Over ‘Weak’ US Finances”, Chief Investment Officer web site, 2026-Jan-01. ↩

2: Reuters Staff, “Swedish pension fund Alecta cuts US Treasury holdings, citing policy uncertainty”, Reuters, 2026-Jan-21. ↩

3: Weekend Editor, “Stock Diversifiers: Treasury vs Corporate Bonds?”, Some Weekend Reading blog, 2021-Jun-07. ↩

4: Weekend Editor, “The Weekend Retirement Portfolio”, Some Weekend Reading blog, 2021-Jun-19. ↩

5: Weekend Editor, “A Weekend Retirement Portfolio for the Trump-Revenant Era”, Some Weekend Reading blog, 2025-Feb-10. ↩

6: Weekend Editor, “Some More Revisions to the Weekend Retirement Portfolio”, Some Weekend Reading blog, 2025-Jun-11. ↩

7: Weekend Editor, “An Even More Defensive Weekend Retirement Portfolio”, Some Weekend Reading blog, 2026-Jan-02. ↩

Candlemas

This past Sunday, 2026-Feb-02, was a minor and usually unremarked holiday in the Christian canonical calendar: Candlemas.

Like most such holidays, it’s sort of pasted on top of an older Roman holiday, in this case Lupercalia.

Traditionally, Candlemas celebrated the presentation of Jesus at the Temple 40 days (inclusive) after his birth, and the ritual purification of Mary. It thus represents the end of the Christmas part of the canonical calendar, and in some places was the occasion for removing Christmas decorations. (In other places, they were removed on Twelfth Night. Here at Château Weekend, the Weekend Editrix and I have differing opinions on this subject. I rather like the lights on the long, dark nights, and hence want to hold out for keeping things going until Candlemas. She, on the other hand, notes that New Year’s Day is, in Japan, a Very Big Deal with its own decoration requirements, and wants the other stuff out of the way as soon as possible.)

The name “Candlemas” comes from having new candles in church, and having domestic candles blessed for use throughout the year. There’s a whole light-sharing thing going on, though sometimes I suspect it’s just a matter of, “It’s dark. It’s cold. We want to have a holiday about sharing light and warmth.”

That works for me, too.

Conclusion: It’s good to seek wisdom & light, and it’s good to be with your neighbors.

Weather Divination by Hibernating Rodents

Then the history takes a turn for the weird, which is how you know it’s true history.

The candle-blessing thing made its way to Germany, where the locals decided that if it was sunny on Candlemas, as measured by the ability of a hedgehog to see its shadow, then more winter was on the way. Just why they decided this is left as an exercise for the reader.

Later, many of the settlers in the US state of Pennsylvania came from Germany, so they brought this custom with them. And that’s when it gets really weird. As always, XKCD has the goods, in this case XKCD #3202, shown here. Munroe’s pointing out the absurdity of weather divination from shadows of usually hibernating rodents, as well as the more modern film comedy, Groundhog Day, which involves inexplicable time loops instead of, or in addition to, inexplicable weather divination by rodents.

As to why it’s now a groundhog and not the original German hedgehogs & badgers, the XKCD mouseover text offers the usual surreal ‘explanation’:

Originally, the ceremony used a variety of rodents and mustelids, but over time most people agreed it made sense to standardize on a specific individual ground squirrel in Pennsylvania.

(There’s a lot to be said of the alternative, and saner, French tradition: one simply eats crêpes on this day, “La Chandeleur”. I think the groundhogs would also prefer we do that, and just left them to hibernate.)

Still, it’s become a big deal here.

The Pennsylvania town of Punxsutawney, population about 5700 and otherwise unremarkable as far as I can tell, is the epicenter. They have a ceremony in which they announce whether “Punxsutawney Phil”, as he is inevitably called, has seen his shadow or not. (I have no idea how they know what the groundhog sees or does not see.)

As you can see here, the ceremony involves handling an otherwise hibernation-adjacent groundhog in front of news cameras by a rather large number of older white men, mostly bearded, all in top hats. It’s difficult to know what the groundhog makes of all that. It’s difficult to know what I should make of all that.

This year, they declared that the shadow was indeed seen, and thus there would be 6 more weeks of winter. The accompanying temperature forecast for the month of February from the National Oceanographics and Atmospheric Administration (what’s left of it), agrees that the eastern half of the US will be colder than usual.

Still… are groundhogs at all accurate in this regard? I mean, there must be some reason that people have held on to this custom, beyond just the surreal fun of it!

I am (not at all reliably) informed that this mishegoss has been going on for 139 years, and that the groundhog has been accurate about 35% of the time.

Sniff… sniff… That smells like data!

We know what to do with data, here on this Crummy Little Blog That Nobody Reads (CLBTNR).

The Null Hypothesis is always something of the form “there’s nothing going on here”. In this case, it’s a binary decision (“more winter” vs “less winter”). So if the weather prediction is a guess, then it should be right about 50% of the time. Anything which deviates from that (up or down!) indicates that something is happening, which is the Alternative Hypothesis.

So we performed a test of proportion in R, as shown here.

The result is shown in the 2 red boxes:

• The probability that the predictions are truly random coin flips, and we still got it right only 35% of the time in 139 tries is very tiny: $p \sim$ 0.000056, or about 5 one hundredths of one percent.

  In other words, there is not a chance we should buy the Null Hypothesis!

• The probability of a correct prediction at 35% after 139 tries has a 95% confidence interval of 27.2% – 43.6%.

  Note that this does not overlap 50%!

Conclusion: Weather divination by rodent is statistically significantly worse than random. Either:

• That rodent is lying!

  Maybe he’s mad at being awoken from a perfectly good hibernation, or is just scared of all the old white guys with beards & top hats. If they woke you out of a sound sleep and waved you around in the sun in front of cameras, you’d be a mite tweaked too, I’ve no doubt.

• That poor, innocent rodent has been miscalibrated!

  We’ve been reading his predictions backwards for 139 years: if we just decided seeing his shadow meant early spring, then he’d have been correct a very solid 65% of the time.

From this we learn that: (a) accuracy of prediction is uncannily not one of the things people care about, and (b) we can nonetheless seek wisdom & light by looking objectively at data.

So far, the Candlemas theme of seeking wisdom & light is holding up. (Sort of.)

Sportsball and Its Discontents

There is, alas, in the US, yet another ritual at this time of the year, involving sportsball. I try very hard to speak of the Super Bowl in terms that are only mildly derisive, but I often fail at that level of restraint.

The only interesting fact about the Super Bowl for me is that they are mysteriously numbered consecutively with Roman numerals. This year is Super Bowl LX, i.e., the 60th iteration of this ritual of concussions and puzzlement over Roman numerals.

Someone showed me a Google Trends plot of queries for the Super Bowl and how to read Roman numerals over the years, showing uncanny correlations. However, that particular graph seems to be at least exaggerated, and thus is not in good odor at Snopes.

But I couldn’t resist checking the data personally, because that’s what we do here on this CLBTNR. The graph shows a 5 year retrospective of queries for the Super Bowl in blue, and queries for how to read Roman numerals in red. They’re both on the same scale, so of course the Super Bowl dwarfs the Roman numeral queries. But… there is a germ of truth here: every year, around Super Bowl time, people wonder how to read MMCMDXLVII or the like. (That example, BTW, is malformed.)

So every year, people do seek a bit of wisdom. Just like this superb owl, raising a claw and reminding us that “No, actually… there’s a great deal more to be experienced in the world beyond sportsball.” (Listen to the owl. He is, after all, a symbol of wisdom.)

In fact, this has been true pretty much forever. The first owl is reminding us of his venerable colleague, possibly an owl forebear of his, shown below him. This is a bit of cave art is from the Grotte Chauvet-Pont d’Arc, or Chauvet Cave, in France. It was apparently a bustling scene of Upper Paleolithic life, but then fell out of use and was undiscovered until 1994-Dec-18. It contains some of the best preserved ancient cave paintings currently known to humanity.

This especially Superb Owl painting is thought to be about 32,000 years old. To compare with the age of the Super Bowl, I remind you that in Roman numerals one uses a vinculum, or bar above the numbers, to mean “times a thousand”. You’d write XXXII for 32, and then put a line over it for 32,000.

So, which ya gonna watch: a mere Super Bowl LX or a Superb Owl $\overline{\mbox{XXXII}}$?

Conclusion: We can look up from the sportsball gladiatorial ceremonies, and celebrate Superb Owl Sunday by looking at some of these absolutely gorgeous animals, traditionally symbols of wisdom.

(And yes, ‘Sportsball and Its Discontents’ is yet another Nerd Tribe joke. Do not tell me you are surprised by this.)

The Weekend Conclusion

Coulda been worse; just be thankful I didn’t go with Super Bowel as a metaphor.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

Nope.

Measles in the US in 2026

Now that RFKJr is making war on public health in general and vaccination in general, perhaps we should check in on the data to see the fruits of his labor.

The data journalists at CNN have been collecting data from (what’s left of) the CDC, as well as from Johns Hopkins and the Center for Outbreak Innovation. At least we still mostly have these data, and can see what’s going on (though I expect that possibly the CDC data reporting may be shut down based on what’s happening, q.v.).

They’ve made a little interactive tool that shows you the cumulative cases of measles in the US, as of the current date. ^[1] Here’s what it’s showing as of today, 2026-Feb-01:

• The horizontal axis is time within a given year.
• The vertical axis is the total number of measles cases seen so far that year.
• The curves shown are for 2023, 2024, 2025, and now the first month of 2026.

The obvious and disturbing conclusion is that 2023 and 2024 were sort of ok, 2025 was a major disaster of public health, and 2026 is shaping up to be far, far worse. We remind everyone that measles is the most contagious disease known to humanity, with $R_0 \sim$ 12-18. That means ever infected person, absent vaccinations and quarantines, will infect 12-18 others. As we’ve analyzed before on this Crummy Little Blog That Nobody Reads (CLBTNR), that means to stop an outbreak you need vaccination rates greater than $1 - 1/R_0$, or about 91% – 94% of the population. That’s why, Chez Weekend, we got MMR boosters last spring: idiots are no longer getting vaccinated and thus posing a risk to the rest of us.

This coming year will be a very difficult one, from the perspective of avoiding the avoidable illnesses.

You can see the pattern of childhood vaccinations at kindergarten age in this map, accompanying the CNN measles reporting tool.

We’re pretty happy about the state of New England, where Château Weekend finds itself. (Ok, New Hampshire, as always, is a conservative laggard. Vermont is a bit more puzzling.) But many other states, in the Deep South and the Midwest, seem to be playing roulette with their children’s health by not getting measles vaccinations.

Honestly, I just don’t understand why that’s not grounds for a charge of child abuse.

ICE Captivity: Maggot-Infested Food, Dangerously Poor Sanitation, No Medical Care, Beatings, and Now… Measles

We’ve known from multiple reports that ICE detention is downright barbaric, more the creation of sadistic thugs than of a civilized nation. All the reports say people sleep on concrete floors without blankets, the food is infested with maggots, the sanitation facilities have far too few showers & toilets, so the result is stink and disease.

It also appears that this is accompanied by beatings. A recent report out of Minneapolis ^[2] told of a man taken into ICE custody, and then taken by ICE to a hospital 4 hours later. This is what the Associated Press got out of interviews with a doctor and 5 nurses:

• The patient was taken into custody with a self-issued warrant from ICE, not a judge. So the detention is legally questionable from the get-go.
• He had a black eye, deeply swollen face, bleeding, and was delirious to the point of having difficulty talking.
• Imaging showed that his skull was fractured in 8 places, and that he had 5 brain areas with life-threatening hemorrhages.

Upon being asked, ICE officers said he was handcuffed and “purposefully ran head-first into a brick wall”. Now, it is physically impossible to get multiple skull fractures on both the left and right side from running head-first into a brick wall with ones hands cuffed behind one’s back. The first time would have incapacitated him, let alone left him in a position to do so multiple times and cause multiple hemorrhages.

“It was laughable, if there was something to laugh about,” said one of the nurses, who spoke to The Associated Press on the condition of anonymity because they were not authorized to discuss patient care. “There was no way this person ran headfirst into a wall.”

This man was, in the opinion of the attending doctors and nurses, clearly tortured.

After all, which is the more likely scenario:

• An acrobatically talented and physically durable prisoner ran into a brick wall multiple times, giving himself multiple life-threatening injuries, or
• ICE just beat him nearly to death, got scared, took him to a hospital, and then lied about it?

Hint: Any scenario which involves ICE lying is probably the more likely scenario.

This is the eternal response of abusers everywhere: blame the victim. He somehow beat himself almost to death, while ICE officers were watching helplessly.

Isn’t that bad enough? Clearly not, in this worst of all possible worlds.

Two different sources report ^{[3] [4]}, and DHS confirms, that measles has broken out in the Dilley Immigration Processing Center (ICE detention), in Texas. When you’re being fed food infested with parasites, have less sanitation than livestock in a crowded barn, sleep on cold concrete, and are fsubject to beatings, measles will make everything much, much worse.

Again, as the most contagious disease known to humanity, we expect this to rip through the ICE detention center and likely kill many. Do you want to take bets on what the MMR vaccination rate is among ICE detainees? (Or among ICE guards, for that matter?)

We note that this center detains children, currently over 400 of the 1200 detainees.

And it’s not just the Texas facility. An independent report documents another measles outbreak in Florence, Arizona. ^[5]

Far from quarantining the outbreak to stop the spread, ICE officials were shipping detainees on buses to Newark and Philadelphia, almost ensuring the spread of measles to those facilities.

ICE officials, of course, admit nothing. However, they did say something very peculiar: instead of releasing detainees to a local church which has customarily taken care of newly released persons, they were being released to a bus depot, apparently so they could go infect someone elsewhere (emphasis added):

Pastor Hector Ramirez, of Iglesia Cristiana el Buen Pastor in Mesa, said his church has been receiving immigrants released from Florence and Eloy detention centers since 2018.…

But later, Ramirez got an email saying 11 migrants would instead be released to the Phoenix bus depot, rather than his church, to ensure his staff wouldn’t risk exposure to measles.

“He told me, ‘Knowing that your volunteers are (older) adults and not wanting to expose them, we’re not going to bring them to your church,’” he said.

So they know there’s exposure risk, and they’re just encouraging people to get on buses instead of going to the local group that normally takes care of new releases? Just… cause disease elsewhere?!

Now, how could ICE make this situation worse?

Well, how about refusing to pay for medical services for detainees? A report from The New Republic ^[6] says ICE has accrued hundreds of millions of dollars of unpaid medical bills for healthcare provided to detainees.
Furthermore, ICE is not only refusing to pay for medical care, but outright refusing to allow medical care in the first place:

To be clear, ICE is not simply not paying for detainees’ medical treatment: Multiple reports suggest they are not providing it at all, even though federal law requires them to do so. Georgia Senator Jon Ossoff released a report in October documenting at least “85 credible reports of medical neglect” at U.S. detention centers.

As a result, people in detention are dying, whether of disease, beatings, or outright murder by ICE agents:

Seven immigrants died in ICE custody in December, making it the deadliest month since Donald Trump returned to the White House. And 2025 was the deadliest year for immigrants in detention since 2004.

So far, January is on track to be even worse: At least six people have already died in ICE custody this year, including one man who reportedly was choked to death by an ICE agent.

ICE is, however, not without a response. It’s an evil response, but still a response, as pointed out by epidemiologist Elizabeth Jacobs:

Note the change in future direction of ICE Health Services: from “direct patient care” to “assessing alien’s [sic] fitness to travel as they prepare for deportation”. As proof, the original ICE Health Services statement is archived here, while the new one is here. Read them and snapshot them now, before ICE deletes the evidence, as is the custom of their tribe.

This amounts to making sure people can survive a deportation flight, so they will just die somewhere else. Jacobs’s comparison to Mengele is not far off.

The Weekend Conclusion

RFKJr is determined, by his vaccine policies, to shoot himself in the foot with a giant footgun. The nature of public health being public, this means he will shoot your foot also. ICE is just penning people up in horrific conditions, beating them, murdering some of them, denying health care, and hoping an institutional pandemic will commit mass murder for them.

Republicans: Are you comfortable with that? Because you voted for that, as was clearly stated in the campaign before the election last year.

In the US, 1/3 voted against this, 1/3 voted for it, and 1/3 couldn’t be bothered to vote. I’m not sure which of the last 2 categories bothers me more.

(Ceterum censeo, Trump incarcerandam esse.)

Addendum 2026-Feb-10: Tuberculosis, Too?!

Apparently that was not enough. Now comes a report that at an El Paso ICE detention facility, there is both COVID-19 and tuberculosis ^[7]:

Two cases of tuberculosis and 18 cases of COVID-19 were recently identified at Camp East Montana, according to El Paso city officials and Congresswoman Veronica Escobar.

Of course, ICE is in full denial & lying mode, as is the custom of their tribe:

Tricia McLaughlin, a Department of Homeland Security spokesperson, and other ICE spokespeople did not respond to detailed questions Saturday. More than 24 hours later, McLaughlin denied in a statement that tuberculosis cases are currently present at the tent camp.

It turns out that they were… simply moved to another camp, so their existence could be denied. This is the same detention center where (a) Geraldo Lunas Campos died after what ICE called “experiencing medical distress”, (b) which they then later claimed was a suicide attempt, and (c) the El Paso medical examiner now rules was a homicide in which ICE agents put too much pressure on his chest and suffocated him.

This utter contempt for human life is like the New York City situation, when a court ordered ICE to stop the inhumane conditions in a detention facility on the 10th floor of 26 Federal Plaza: inedible food, sleeping on concrete floors, so few toilets they’re soaked in sewage, and constant sickness. ICE’s response was… moving prisoners to another floor, claiming that the court order only applied to the original floor! ^[8] They then denied having done this.

Of course they lie about it, both to a Congressman and to the court:

In a statement provided to amNewYork, Congressman Dan Goldman, a longtime critic of the courthouse detentions, condemned the revelation.

“ICE is not only lying to the Court, but they are lying to me,” Goldman said.

Look, just admit it: these are death camps. They are trying to make as many detainees die as they can, short of actual executions. Sewage, food infested with worms, no medical care, and now a trifecta of COVID-19/measles/tuberculosis… these are simply killing people.

Depraved neglect at this level is simply murder.

ICE employees must, in the future, be tried and face long prison terms if convicted.

Notes & References

1: AL Matthews, et al., “Tracking measles cases in the United States”, CNN, 2026-Jan-08.

Data used here is the update as of 2026-Feb-01. ↩

2: M Biesecker, et al., “Takeaways from AP report on ICE claims that immigrant shattered his skull running into wall”, AP News, 2026-Jan-31. ↩

3: J Warner, “Measles outbreak at Texas immigration detention facility confirmed by DHS officials”, News 4 San Antonio, 2026-Feb-01. ↩

4: S Koithan, “Source: Measles outbreak reported at ICE’s Dilley family detention facility”, San Antonio Current, 2026-Feb-01. ↩

5: E Bregel, “Measles outbreak at ICE detention centers in Arizona prompts quarantine”, Tucson.com, 2026-Feb-01. ↩

6: E Olmsted, “ICE Has Cut Its Detainees Off From Medical Care”, The New Republic, 20226-Jan-20. ↩

7: C DeGuzman & L Kriel, “Two cases of tuberculosis detected at Camp East Montana El Paso ICE facility”, Texas Tribune via El Paso Matters, 2026-Feb-09. ↩

8: D Moses, “Multiple floors of 26 Federal Plaza in Lower Manhattan now being used to detain immigrants arrested by ICE, feds admit”, AM New York, 2026-Feb-10. ↩

The Motivation

This Crummy Little Blog That Nobody Reads has for some time been having… opinions about a variety of issues. One of them is the Russian invasion of Ukraine. ^{[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16]}

We’ve been collecting data on Russian casualties in Ukraine for quite a while. A timeline:

• 2022-Feb-24: Russia invades Ukraine, expecting a 3-day “special military operation.”
• 2023-Jan-22: Realizing more than 3 days had passed, your humble Weekend Editor began collecting data, for 116 consecutive days, on Russian casualties and equipment loss as reported by the Ukrainian Ministry of Defence. “Equipment” meant things such as trucks, tanks, artillery, and so on.
  • And, apparently, submarines. In a land war. With a country that has no navy. Someday, after Ukraine wins and rebuilds, that’s going to be hilarious. Zelensky, as a former comedian, will be well placed to Explain It All.
  • We did lots of correlation analyses between the various equipment types, as well as regressions.
  • But in the end, we only really stuck with the casualties.
• 2024-Apr-10: We began collecting casualty data on the date for each increment of 100k. (With one exception at 450k. That’s how you know it’s real data: you can see my mistakes, too!)

The plot shown here is one of the results:

• The axes:
  • The horizontal axis is time, measured in number of days since 2023-Jan-22.
  • The vertical axis is the number of soldiers killed.
• Data points:
  • The blue points, in the lower left, are the initial 116 consecutive days of data collected.
  • The red points, sparse and in the upper right, are the days data was collected from 2024-Apr-10 to the present. The increments on the vertical axis are approximately 100k. (The exception is the first red data point, which is only 50k below the next one. Mea maxima oops.)
• Model fits:
  • The dashed line is a least squares fit to the first 116 days.
  • The gray band around it is the prediction confidence limit (the uncertainty if you use the regression line to predict 1 more point).
• The puzzle: note that all the red points are above the regression line, and clearly on a more steeply inclined upward trend.

Research question: Is this statistically credible evidence that something happened around day 420 or so (2024-Mar), to make Russian death rates increase?

Possible causes might be Russian reliance on human wave/meat grinder tactics that burn up their own soldiers, or Ukraine getting deadly clever about drone use, or several other things. We won’t explore the cause here; we just want to know if the data justifies that something happened, whatever the particulars.

Segmented Regression

Basically, it looks like the data is quite linear in time, it’s just that there’s a kink in the line around day 410, when the line bends upward but continues to be linear.

There’s a technique for that in statistics: segmented regression (also called piecewise regression, broken-stick regression, and lots of other names). In addition to the Wikipedia page just linked, there’s a nice tutorial slide deck by Alex Kaizer that’s quite readable.

The general idea is to consider regression models of the form:

where:

• $t$ indexes data points in time,
• $\theta()$ is the Heaviside step function (0 for negative argument, 1 for positive argument, here used as an indicator for “after day $\psi$”, i.e., the fancy-pants modeling language for an “if” statement),
• $\psi$ is a parameter for estimating the time at which the kink occurs, and
• $\epsilon \sim N(0, \sigma^2_{\mbox{Soldiers}|\mbox{DayNum}})$ is the error usual error term, normally distributed around 0 with the conditional variance shown.

If we consider expectation values, the interpretation is immediately obvious:

So $\beta_1$ is the slope before the kink, $\beta_1 + \beta_2$ is the slope after the kink, and $\beta_0^*$ is a new intercept depending on the slope difference and the location of the kink in a way about which we generally do not care, for most purposes.

Modeling the Data

There are perfectly reasonable parameter estimation methods for such a model, that will tell us $\beta_1$, $\beta_2$, and $\psi$ along with their uncertainties. We used the segmented library in R. The script, along with the original linear model script, and all the datasets are available here for your peer review pleasure. ^[17]

• We first tested objectively whether there was need for a kink in the linear model with the standard Davies Test, which basically tests the difference in slopes for significance, for a variety of choices of $\psi$ and a number of points on each side of it. If that had not come out significant, no further analysis would have been necessary and we would have been content with the original linear model.
• We did not attempt regularization via LASSO or equivalent, because there just aren’t any parameters to drop. Instead we compared our kink model to the overall linear model, to make sure our additional model complexity (2 more parameters, $\beta_2$ and $\psi$) was earning its keep by lowering the root-mean-square error of the model.
• We did 3-fold cross-validation, to make sure we were not over-fitting. Given that there are only 9 red points in the plot above, we did not dare go for more folds. We report below the performance of each of the 3 folds, and a final training run on the entire dataset.

Results

Need for a Kink in the Model

Davies test was ridiculously statistically significant, with $p \sim 1.62 \times 10^{-72}$. (R generally will not report a $p$ value less than $2.2 \times 10^{-16}$ without blushing, so that’s what appears in the transcript. We reached inside the data structure of the Davies test result to see the actual answer.)

So that’s very significant, and we can proceed to fitting the segmented models.

Cross-Validated Regressions

The results of 3-fold cross-validation and a final fit on the entire dataset are shown here. The RMS errors are, of course, the out-of-sample errors on the test fold (except for the final global fit). The slope 2 reported here is $\beta_1 + \beta_2$, i.e., the actual slope of the line after day $\psi$. “Linear” refers to a simple linear fit with no kink, for comparison.

• The kink position $\psi$ stays quite stable across folds and in the final model, especially compared to the estimated standard deviation. This encourages us to believe that the kink is more or less where the model says it is.
• The 2 slopes are also pretty consistent across folds and in the final model, though the variation of slope 2 seems to be a bit outside the estimated standard deviation. I would say this is due to there being fewer data points (in red) after $\psi$, but that should have been encoded in a larger standard deviation?
• Both the linear model and the kinked model show excellent $R^2$. There’s not a lot of room to see improvement here, though the kinked model does get an extra 0.9% or so.
• The kinked model really begins to shine when we look at the RMS error, particularly on the out-of-sample test folds. It is dramatically less, like a factor of 5 or so.

The stability under cross-validation and the dramatic reduction in RMS error (compared to a simple linear model with no kink) make us believe the kinked-line model is the correct choice, beyond a simple linear model.

Interpretation

Finally, here’s a plot of the model and the data, so you can see what’s going on (click to embiggen).

• The axes:
  • The horizontal axis is time, measured in number of days since 2023-Jan-22.
  • The vertical axis is the number of soldiers killed.
• Data points:
  • The blue points, in the lower left, are the initial 116 consecutive days of data collected.
  • The red points, sparse and in the upper right, are the days data was collected from 2024-Apr-10 to the present.
• Model fits:
  • The vertical line shows the position of $\psi$, the day of the kink at 2024-Mar-08. The vertical dashed lines to either side are the 95% confidence limits, at 2024-Feb-18 and 2024-Mar-26. Basically, they’re pretty tight, so we believe the kink is about where the model says it is.
  • The solid black line is a least squares fit to the entire data, including the kink.
  • The gray band around it is the prediction confidence limit (the uncertainty if you use the regression line to predict 1 more point). I’m more than a little uncomfortable with how narrow this uncertainty band is, its shape around the kink $\psi$, and how it doesn’t seem to grow enough at the edges of the data. However, it’s what the segmented library reports, and I haven’t investigated further. (Comments welcome!)
  • The dotted line on the right shows what the trend would have been without a kink, i.e., it continues the fit from before the kink.

Basically, the kink model follows the data much more closely, explaining why it has a much lower RMS error compared to a single straight line.

The ratio of kill rates before and after the kink is 1237.30 / 699.58 = 1.76. That is, the Ukrainians apparently got 76% more efficient at killing Russians on or about 2024-Mar-08.

The Weekend Conclusion

Yes, the Ukrainians did become about 76% more efficient at killing Russian soldiers on or about 2024-Mar-08.

The evidence for this is very good… for values of “good” that include fascists invading their neighbors, which is sadly now widely relevant.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: Weekend Editor, “Another Grim Anniversary”, Some Weekend Reading blog, 2023-Mar-02. ↩

2: Weekend Editor, “Do the Ukrainian Reports of Russian Casualties Make Sense?”, Some Weekend Reading blog, 2023-Apr-15. ↩

3: Weekend Editor, “Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-01. ↩

4: Weekend Editor, “Updated Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-09. ↩

5: Weekend Editor, “Updated${}^3$: Ukrainian Estimates of Russian Casualties Hit 200k”, Some Weekend Reading blog, 2023-May-17. ↩

6: Weekend Editor, “Ukraine Invasion: 250k Russian Dead”, Some Weekend Reading blog, 2023-May-17. ↩

7: Weekend Editor, “Tacitus in Ukraine”, Some Weekend Reading blog, 2023-May-25. ↩

8: Weekend Editor, “Casualties in Ukraine: Grief Piles Higher & Deeper”, Some Weekend Reading blog, 2024-Apr-10. ↩

9: Weekend Editor, “Post-Memorial Day Thought: 500k Russian Dead in Ukraine “, Some Weekend Reading blog, 2024-May-31. ↩

10: Weekend Editor, “Ukraine: 600k Russian Dead”, Some Weekend Reading blog, 2024-Aug-27. ↩

11: Weekend Editor, “Ukraine War: 700k Russian Dead”, Some Weekend Reading blog, 2024-Nov-04. ↩

12: Weekend Editor, “Ukraine War: 800k Russian Dead”, Some Weekend Reading blog, 2025-Jan-08. ↩

13: Weekend Editor, “Ukraine War: 900k Russian Dead”, Some Weekend Reading blog, 2025-Mar-21. ↩

14: Weekend Editor, “Ukraine War: 1,000,000 Russian Dead?!”, Some Weekend Reading blog, 2025-Jun-12. ↩

15: Weekend Editor, “Ukraine War: 1,100,000 Russian Dead”, Some Weekend Reading blog, 2025-Sep-22. ↩

16: Weekend Editor, “Ukraine War: 1,200,000 Russian Dead”, Some Weekend Reading blog, 2025-Dec-31. ↩

17: Weekend Editor, “R script for analysis of Russian Casualties in Ukraine”, Some Weekend Reading blog, 2026-Jan-28.

There is also a transcript of running the script, for your review.

The data driving this analysis, in .tsv format, is also available for review.

The data driving the original analysis, in .tsv format, is also available for review by the persistent skeptic.

This whole mess depends on some idiosyncratic subroutine libraries of our own construction, graphics-tools and pipeline-tools. We are happy to supply these to exceptionally persistent skeptics who wish to reproduce these results. :-) ↩

A Study of AI Users and Their Personality Types

Somewhere I came across a blog by David Gerard called Pivot to AI, largely consisting of rather well-reasoned critiques of AI and a hefty side of snark. (Motto: “It can’t be that stupid, you must be prompting it wrong.”) One recent article ^[1] is about how much people actually, measurably use AI, and what kinds of personality types are associated with that.

You can probably take a guess where this is going, given the illustration shown here: virtual reality goggles clamped firmly in place by crab-like arms around the back of the head, a tube to interfere with breathing, and a tentacle about the neck. This is clearly a riff on the face-hugger monsters such as those in the old 70s horror flick Alien.

He’s reporting on a recently published – and thus peer-reviewed – paper by McKinley, et al. ^[2], in which they studied 2 pretty good-sized populations, measuring amount of AI usage and administering 2 different personality type tests to see what sort of people used AI more than others. (NB: McKinley, the lead author, is a PhD candidate. If this very good paper is any indication, she will have a heck of a thesis and a good start to her career!)

There’s another summary of the same paper and some brief interview material with McKinley, by Dolan at PsyPost ^[3].

The results are about what I’d hoped (LLMs are really not very popular) and feared (LLMs tend to get used by people who are more Machiavellian, narcissistic, or psychopathic). In other words, the good news is most people ignore LLMs, but the bad news is that bad people use it. This makes a degree of sense: LLMs are basically BS engines, so BS artists probably regard them as valuable time-savers.

Prolegomena

They studied 2 separate populations:

• Students from 2 universities, $N$ = 499
• General public (selection criteria somewhat unclear to me), $N$ = 455.

They did not rely on self-reports of use of AI, though they did record that too. (See below on how inaccurate the self-reports were.) Instead, they filtered for subjects who used the Chrome browser, and were competent to install their plugin to measure web site usage. This has 2 effects: by giving up on measuring phone/app usage, they’re biasing it to older subjects (“the desktop is for geezers”, as one commenter put it), and even so they are only accepting those with enough technical competence to install their plugin. Both of those issues will have to be revisited in any followup studies attempting replication, though the authors are up-front about it.

The study period was for 3 months.

They annotated the web sites visited by subjects in a couple dozen categories, which we can summarize here as “AI” or “not AI”. The initial AI sites were from a repository curated by AI researchers. For the rest, they (alas!) used ChatGPT to classify the web sites according to a widely used taxonomy from the Interactive Advertising Bureau. While I despise the idea of trusting ChatGPT to tell the truth about anything, they did at least have 2 people hand-check a random sample of 200 web sites, finding only 1 error, a web site which could not be accessed for assessment. Maybe good enough for a start, but it’s a weak point that makes me itch!

They also administered some well-thought-of psychological tests to the participants:

• The TIPI, or ten-item personality inventory, is a version of the well-regarded Big Five personality traits. It rates subjects on scales for Extraversion, Agreeableness, Conscientiousness, Emotional Stability, and Openness to New Experience. It has high reproducibility.

  You can take the Big Five test for yourself to see if it seems to capture what you know about yourself.

• The SD3, or short dark triad personality test, measures for the Dark Triad personality traits of Machiavellianism, Narcissism, and Psychopathy. These well-defined terms are personality traits with well-documented clinical correlates, e.g., diagnosing Narcissistic Personality Disorder, Antisocial Personality Disorder, and so on.

  You can take the Short Dark Triad test yourself to see if you recognize anything about the darker side of yourself.

• Other tests measured attitudes toward AI, its ease of use, perception of its usefulness, general technology acceptance, political ideology, etc.

(They also computed Cronbach’s $\alpha$, a measure of internal consistency/reliability of the tests; we won’t go into detail about that.)

There were a lot of measurements, but the two that stand out to me are:

• What personality traits predict more use of AI?
• If we separate the prolific AI users from the rest, how are they different in personality traits?

Since the distributions of AI usage were decidedly non-normal (more like a power law?) they decided to use of Spearman rank correlation $\rho$. (I hope this means they rank-ordered the data first, but the word salad was a bit unclear to me.)

Results: Frequency of Use of LLMs & Personality Type Correlates

Here’s the observed distribution of number of “AI” sites visited, for the student population (top) and general public (bottom). Note the difference in horizontal scales: the general public used AI sites much less. This is over the whole study period, which remained pretty constant; there were no observable trends over time.

The authors note this is decidedly non-normal, and thus punted to rank-order statistics like Spearman’s $\rho$. That’s… sort of okay, I guess? I’d have tried some distribution tests to see what’s at least close to the observations. They speculate it’s a power law, but do no analysis to test this. My favorite method for power laws in empirical data is from Cosima Shalizi’s group ^[4], which not only gives stable methods for estimating the parameters but recommendations for other distributions to test and compare with likelihood ratios.

That’s not a fatal flaw in the paper, and the rank statistic tactic is probably acceptable. But in the future, or even in a reanalysis of these data, the Shalizi tests could be informative in that they enable more specific statistical methods once the distribution is identified.

Here’s the top-line result: over 90 days, about 1% of the sites visited by students were AI sites, and about 0.44% of the sites visited by the general public. That’s… very low.

Also, when comparing self-reported AI use with measured AI use, they got a Spearman $\rho \sim$ 0.329, with an associated significance of $p \sim$ 0.001. (It seems this was done only in the general public test population, and not for students?) That’s statistically significantly different from 0, but still pretty low. It was a good idea to measure AI use directly, because the self-reports were not accurate. (They do not say if the self-reports were higher or lower than the measurements.)

Conclusion: AI use in both populations is much lower than expected.

Looking at the student population, they computed Spearman correlation of number of AI sites visited with the Big 5 personality types and the Dark Triad personality disorders. The statistically significant ($p \le$ 5%) Spearman rank correlations were as shown here: mild to moderate association, but statistically significant (i.e., reproducible).

They also report that, in the student population, Extraversion on the Big 5 personality test is correlated with both Narcissism and Psychopathy. This leads one to think Narcissism and Psychopathy are the root elements, and bring Extraversion along with them.

In the general population, there was much less AI use and thus it was harder for Spearman rank correlations of AI use with personality measurements to reach statistical significance. Nothing really made the usual $p \lt$ 0.05 cut; the closest was Machiavellianism at $\rho \sim 0.080$, $p \sim$ 0.087.

Conclusion: In younger people, AI use correlates with Extraversion, Narcissism, and Psychopathy scores. In the general public, AI use was low enough that it was hard to tell, though there was a hint at a relationship to Machiavellianism.

Results: Personality Types for Prolific LLM Users

They did another study, focusing on the differences in personality between prolific AI users (more than 4% of URLs during the study period) vs everybody else. Since the AI usage in the general population was pretty low, the prolific population was too small for analysis. So this is just for the student population.

They looked at the test scores between the student prolific and non-prolific AI users, and tested for a difference in mean with a Welch (unequal $\sigma^2$) $t$-test. Commendably, they also tested for effect size with Cohen’s $d$.

Obviously, the limiting factor for statistical significance is the small number of prolific users:

• Prolific: N=20
• Non-Prolific: N=479

There were no significant differences in the Big 5 personality factors ($p \gt$ 0.15), i.e., the prolific AI users were about the same in Extraversion, etc.

However, it’s quite disturbing that all 3 of the Dark Triad personality disorders were statistically significantly associated with prolific AI use (by Welch’s $t$ test). The effect size, according to the usual tables for interpreting Cohen’s $d$, ranged from medium (0.5) to large (0.8).

In the spirit of “correlation is not causation”, we must mention that we do not know if Dark Triad people tend to use AI more (“game recognizes game”, so BS artists like BS engines), or whether prolific AI use made them that way.

This is a serious question: as we’ve written before ^[5] on this Crummy Little Blog That Nobody Reads (CLBTNR), there is now significant anecdotal evidence of extreme AI use causing mental illness.

Either way, this result is alarming.

Conclusion: Prolific AI users in the student population scored higher on tests for all 3 of the Dark Triad personality disorders. This was both statistically significant and a medium to large effect size.

The Weekend Conclusion

We’ll leave the final word to Gerard’s Pivot to AI post, since I kind of cringe at using the sort of vocabulary required for sufficient emphasis:

So AI is not actually popular, and AI users are unpleasant assholes.

Cruder than I’d put it, but you won’t forget it.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: D Gerard, “AI is not popular, and AI users are unpleasant asshats”, Pivot to AI blog, 2025-Oct-10. ↩

2: E McKinley, et al., “Evaluating Artificial Intelligence Use and Its Psychological Correlates via Months of Web-Browsing Data”, Cyberpsych Behavior & Soc Net 28:10, 2025-Oct-14. DOI: 10.1177/21522715251379987. ↩

3: EW Dolan, “Most people rarely use AI, and dark personality traits predict who uses it more”, PsyPost, 2025-Oct-12. ↩

4: A Clauset, CR Shalizi, & MEJ Newman, “Power-Law Distributions in Empirical Data”, SIAM Review 51:4, 2009. DOI: 10.1137/070710111.

NB: The preprint on arχiv is not paywalled. ↩

5: Weekend Editor, “AI LLMs: A Way to Make Yourself Crazy… Literally!”, Some Weekend Reading blog, 2025-Aug-16. ↩

Our Priorities

I’ve forgotten who told me this, years ago. It was something like: “Show me where you spend your money and your time, and I’ll tell you what your priorities are.” I both love and hate that saying. On the one hand, it invites introspection about how well one lives ones values. On the other hand, it strongly invites guilt in someone like me prone to depression, anxiety, and excessive scrupulosity.

Still, it seems like we ought to be able to do something like that society-wide: do our social priorities reveal our values?

This graph ^[1] was prepared by Mark J Perry, of the American Enterprise Institute. Let’s get this out of the way first: I despise the American Enterprise Institute. They’re a hard-right think-tank, issuing mostly propaganda papers that undermine anything like sensible policies in health care, equality, … You name it, if I’m for it they’re guaranteed to be against it with some plausible-sounding reason that facile, glib, and evil.

I say this so you will take me seriously when I say this graph captures… something… important about the American zeitgeist.

• The horizontal axis is time in years, 2000-Jan to 2022-Jun, so 22 years.
• The vertical axis is the relative change in price over that time.
• Each curve is for a particular type of goods & services.
• The red curves have increased more than inflation; the blue curves have increased less, or even dramatically decreased.

NB: There’s a bit of wool being pulled over your eyes here, sometimes called the hedonic treadmill. That says the nature of goods changes over time, usually for the better. We become accustomed to that improvement, and often erroneously project it into the past. A car from the 2000 model year is not the same as a care from the 2022 model year!

Most consumer electronics are like this, due to rapid change. Other things are like this too, such as health care: you’d much rather have a cancer diagnosis in 2022 than in 2000, because we can help you a lot better now! So you might expect health care to be more expensive, but then why do you expect consumer electronics to go the other way?

So we shouldn’t take this as absolute truth, and extending it to longer time periods would probably be even more misleading. But for 22 years, let’s think about where prices increased with inflation and where they decreased, and why.

The thing to note is the nature of the goods and services on the red and blue trajectories.

• The blue curves – stuff that’s gotten cheaper in real terms – are mostly physical goods, and in some cases luxury goods.
• The red curves are largely services, like health care, child care, and higher education.

Now, there can be many reasons for that rather dramatic divide.

• The AEI folk will rant endlessly and senselessly about ‘socialism’, claiming that government intervention in health care caused the price increase.

  This is, of course, pernicious nonsense. Western European countries are far more credibly social democratic in their universal health care polices, and they do not see this kind of price increase while seeing better health care outcomes than the US.

  Far more likely is that the price rise is the product of a large number of private entities each seeking ‘their share’ of the large flow of health care money. Look at an itemized health care bill in the US sometime: do you even recognize some of the entities demanding a share of your insurance payment? I often do not!

• A somewhat more likely interpretation is that the services are mostly not tradeable, whereas the physical goods are largely tradeable. The graph covers a time period when there was a lot of relatively tariff-free trade, and thus pricing pressure on manufacturers to be at least as good as the imported stuff.

  Of course, in the US we’ve dismantled that world with the Trumpian tariffs, military violence, kidnappings domestic & foreign, and general bombast. Perhaps in the future we will see the blue curves rise sharply with the impairment of international trade? Or will we see all the curves collapse in a deflationary disaster, like the last time we shut down global trade in the Great Depression?

• But the most likely interpretation, to my non-economist intuition, is that this chart shows us what we care about the most.

  To our blame:

  • We value luxury goods like TVs, computers, and cars a lot, but…
  • We do not value social goods that improve the lives of all of us, like health care, education, child care, clean air & water, and cheap, nutritious food.

  To the extent that this shows us where we spend our time & money making things better, this is a moral insight into the flawed nature of our society.

The Weekend Conclusion

We know better, but we are sadly reluctant to do better.

So let us encourage each other to do better.

I can do better. So can you.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: MJ Perry, “Chart of the Day… or Century?”, Carpe Diem blog at the American Enterprise Institute, 2022-Jul-23. ↩

The Anecdote That Made Me Angry Enough to Sewer-Gaze

This week several things about people’s use of LLMs (“Large Language Models”) really got to me:

• One friend has begun taking religious advice from a chatbot, which seems deeply psychologically wrong to me.
• Another friend, a psychotherapist, has been losing patients to chatbots – some patients seem to prefer the sycophantic BS firehose to an actual compassionate person.

A third item – in somewhat more detail – is an anecdote from the writer John Scalzi ^[1], whose blot I follow because he’s a good raconteur.

He describes the AI chatbots not as “fact-finding machines”, but as “fact-failing machines”, for reasons that should be more or less immediately obvious. Someone asked a chatbot how Scalzi had dedicated a certain book of his, and got a mildly clever answer. But…

• Scalzi never wrote that particular dedication. The chatbot-hallucinated dedication also refers to “my children”, when he’s made it plain he has exactly one child, now an adult.
• So Scalzi asked other chatbots the same question, and got equally deranged answers:
  • One claimed it was dedicated to his daughter, but hallucinated the name from the movie The Fifth Element, which has nothing to do with his actual daughter.
  • Another insisted the dedication was to Scalzi’s wife, which it was not.
  • Another said it was dedicated to “Corey”, but Scalzi has no idea who that might be.
  • Another said the information was not online, when in fact it is.

  • Another said it was dedicated to two other writers, whom Scalzi says he knows, vaguely… but not to the extent of dedicating a book to them! The reaction when Scalzi informed the chatbot that it was wrong?

    When I informed Gemini it had gotten it wrong, it apologized, misattributed The Consuming Fire to another author (C. Robert Cargill, who writes great stuff, just not this), and suggested that he dedicated the book to his wife (he did not) and that her name was “Carly” (it is not).

Basically, all very confident and very, very wrong. That’s the thing about LLMs: they have no relationship with the truth whatsoever, and are very good indeed as BS artists who can make you believe them. This is rhetorical poison.

Scalzi’s advice:

One: Don’t use “AI” as a search engine. You’ll get bad information and you might not even know.

Two: Don’t trust “AI” to offer you facts. When it doesn’t know something, it will frequently offer you confidently-stated incorrect information, because it’s a statistical engine, not a fact-checker.

Three: Inasmuch as you are going to have to double-check every “fact” that “AI”” provides to you, why not eliminate the middleman and just not use “AI”? It’s not decreasing your workload here, it’s adding to it.

Well, that pretty much aligns with what I think.

Now, Scalzi’s a clever fellow, but not a specialist and not a technical thinker. Shall we examine some other more deeply considered technical and business opinions?

What the Business Media are Saying

First, let’s consider what the more reasonable wing of the business press is saying companies are experiencing with their AI efforts.

A Reuters article ^[2] catalogs the frustrations companies still trying to get the things to lead to profits:

Since ChatGPT exploded three years ago, companies big and small have leapt at the chance to adopt generative artificial intelligence and stuff it into as many products as possible. But so far, the vast majority of businesses are struggling to realize a meaningful return on their AI investments, according to company executives, advisors and the results of seven recent executive and worker surveys.

One survey of 1,576 executives conducted during the second quarter by research and advisory firm Forrester Research showed just 15% of respondents saw profit margins improve due to AI over the last year. Consulting firm BCG found that only 5% of 1,250 executives surveyed between May and mid-July saw widespread value from AI.

Some examples:

• One company tried to build an AI wine recommender. Alas, it’s so sycophantic it won’t give a negative recommendation! What good is a recommender who will never say, “You probably won’t like this one”?
• In another example, there was an attempt to make an AI tutor for employees studying Canadian rail safety rules, which is about a 100 page document. The problem: sometimes the AI “forgets” rules (actually, it never understood them in the first place), and other times it just makes up rules out of nothing. Clearly useless, especially in a safety discipline!
• Swedish payments company Klarna rolled out in 2024 an AI they said could do the work of 700 call center service agents. In 2025, they dialed it back apparently because it mostly just frustrated customers.
• Verizon did something similar, but had to pull back after customers hated it.

  “I think 40% of consumers like the idea of still talking to a human, and they’re frustrated that they can’t get to a human agent,” said Ivan Berg, who leads Verizon’s AI-driven efforts to enhance service operations for business customers, in a Reuters interview this fall.

Basically, managers love the idea of firing people. But then they find out the AI can’t actually do the work, and they have to go back to people. As Cory Doctorow said ^[3], now famously:

AI can’t do your job. But an AI salesman can convince your boss to fire you and replace you with a chatbot that can’t do your job.”

Disinformation is a powerful drug.

Next, from The Economist comes an article ^[4] discussing the financial leverage that requires rapid adoption of AI, and the evidence that adoption is in fact flatlining or even decreasing.

This is a crucial issue for the US economy. The big tech stocks are all-in on AI, having leveraged themselves to the hilt and even shuttling money to each other (as we previously wrote in this CLBTNR). That leverage means they better have some extreme earnings, and very soon, to pay off the loans on their data centers, or they die. If they die, then the US goes into a depression because they right now represent a huge fraction of the US stock market.

These are the ‘Magnificent 7’ stocks: Alphabet/Google, Amazon, Apple, Meta/Facebook, Microsoft, Nvidia, and Tesla. If you add Broadcom, Berkshire Hathaway, and the other share class of Google (yes, there are 2; Google is needlessly complex), those are the largest 10 stocks in the US.

As you can see in this plot (I just randomly picked Schwab research as my source; you can find this information literally everywhere), the top 10 stocks in the S&P500 now account for 40% of its value! The plot only goes back 35 years, but considering history even further back, this level of concentration is unheard-of. Since those stocks are now highly leveraged bets on AI, a collapse will make the rest of us pay for the cost of that leverage.

The Economist puts some numbers on it:

From today until 2030 big tech firms will spend \$5trn on infrastructure to supply AI services. To make those investments worthwhile, they will need on the order of \$650bn a year in AI revenues, according to JPMorgan Chase, a bank, up from about \$50bn a year today.

A “mere” factor of 10x increase in earnings is all that’s required!

But it appears adoption is not rapidly increasing. It seems mostly to be a management fantasy:

A survey by Dayforce, a software firm, finds that while 87% of executives use AI on the job, just 57% of managers and 27% of employees do.
…
Changing perceptions of AI’s usefulness could be another reason for the adoption stagnation. Evidence is mounting that the current generation of models is not able to transform the productivity of most firms.

Slowly, those managers are coming to realize their dreams are not coming true:

According to a poll of executives by Deloitte, a consultancy, and the Centre for AI, Management and Organisation at Hong Kong University, 45% reported returns from AI initiatives that were below their expectations. Only 10% reported their expectations being exceeded.

Indeed, something of the opposite sort is happening:

A paper by Yvonne Chen of ShanghaiTech University and colleagues refers to “genAI’s mediocrity trap”. With the assistance of the tech, people can produce something “good enough”. This helps weaker workers. But the paper finds it can harm the productivity of better ones, who decide to work less hard.

That sounds about right: if your job can be done by AI, then it’s a trivial job that needn’t be done. If your job can’t be done by AI, as is likely, then your problem is management hallucinations otherwise.

Some Formal Studies

So much for the unexpectedly grim opinion of the business press. Now let’s look at some more formal academic studies.

From Fortune ^[5] comes a report on an MIT study, alleging a stunning 95% failure rate on corporate AI projects. Fortune’s summary is (emphasis added):

Despite the rush to integrate powerful new models, about 5% of AI pilot programs achieve rapid revenue acceleration; the vast majority stall, delivering little to no measurable impact on P&L. The research—based on 150 interviews with leaders, a survey of 350 employees, and an analysis of 300 public AI deployments—paints a clear divide between success stories and stalled projects.

The ones that succeed seem to be small startups that do just 1 thing with AI, and nothing else. On the other hand, your humble Weekend Editor is a grizzled old suspicious scientist who thinks it’s probably just easier to claim a huge percent growth in revenue when you’re starting from almost nothing in the first place!

On the other hand, they claim attempts to use LLM AIs in sales and marketing fail, whereas attempts at back-office automation tend to work. (We suspect this is because they can be well-specified?) Those back-office procedures can then be in-sourced and streamlined.

More q.v., but for now simply note that the successful companies are doing what we might term slow layoffs: just not filling positions as people leave. I deeply suspect much of the management interest in AI is because they want to fire people.

Examining the MIT study itself revealed an interesting insight on the front-line vs back-office choice of where to deploy LLMs:

Investment bias: Budgets favor visible, top-line functions over high-ROI back office

Several pages later:

Investment allocation reveals the GenAI Divide in action, 50% of GenAI budgets go to sales and marketing, but back-office automation often yields better ROI.
…
This investment bias perpetuates the GenAI Divide by directing resources toward visible but often less transformative use cases, while the highest-ROI opportunities in back-office functions remain underfunded.

In other words: if you’re doing it for show, you will more likely fail. Don’t let sales & marketing attempt to lead the way.

Another interesting finding: most of the large adoption attempts either fail or don’t meet the needs of the employees who are asked to use them. But a bottom-up approach of letting employees pick and choose small-scale AI uses fails less often:

While official enterprise initiatives remain stuck on the wrong side of the GenAI Divide, employees are already crossing it through personal AI tools. This “shadow AI” often delivers better ROI than formal initiatives and reveals what actually works for bridging the divide.

Behind the disappointing enterprise deployment numbers lies a surprising reality: AI is already transforming work, just not through official channels. Our research uncovered a thriving “shadow AI economy” where employees use personal ChatGPT accounts, Claude subscriptions, and other consumer tools to automate significant portions of their jobs, often without IT knowledge or approval.

Note the last bit: when employees do samizdat AI projects without IT interference, they are more likely to succeed, for some definition of “success”. Don’t fear the SkunkWorks.

The study concludes:

Organizations that successfully cross the GenAI Divide do three things differently: they buy rather than build, empower line managers rather than central labs, and select tools that integrate deeply while adapting over time.

Personally, I think that’s over-optimistic, but it’s what the study authors think.

Another formal study comes from Carnegie-Mellon University. ^[6]

They took a simulation approach, in which they created a virtual company in software. They had computer jobs, sales jobs, HR jobs, financial jobs, and so on. Using Department of Labor databases describing various jobs, they set up a large variety of tasks that needed to be performed, and set loose some AIs to see what they could and could not do.

The disappointing result is most agents fail at most jobs, and some fail at nearly all:

The best of them, Claude 3.5 Sonnet from Anthropic, only completed 24% of the tasks. Google’s Gemini 2.0 Flash came in second with 11.4%, and OpenAI’s GPT-4o was third with 8.6%.

Qwen2-72B, developed by a Chinese AI startup, came in last, completing just 1.1% of the tasks.

In a fascinatingly disgusting development, some of the ways the agents would fail involved lying about what they did:

“Interestingly, we find that for some tasks, when the agent is not clear what the next steps should be, it sometimes tries to be clever and create fake ‘shortcuts’ that omit the hard part of the task,” the researchers noted in their paper.

For instance, when the agent couldn’t find a particular person it needed to contact in the company’s chat platform, it instead renamed another user, giving it the name of the person it was seeking.

Now think about this carefully:

• Would you hire employees who failed ≥ 70% of the time & frequently lied about it?
• If not, why would you even touch an LLM AI that did so?

Some Deeper Business Studies

So far we’ve consulted the opinions of (a) an opinionated novelist (Scalzi), (b) the better end of the business press (Reuters, The Economist), and research universities (MIT, CMU). Now let’s have a look at some deeper business studies.

Boston Consulting Group published some work asking whether there is a widening “AI value gap”. ^[7]

By this they mean whether a company is “AI-future built”, in terms of control flow, accountability, and general architecture capable of realizing AI benefits. Like the MIT study above, they think these architectural differences determine the gains that might be reaped. BCG claims:

• Worldwide, only 5% of firms are so configured.
• They will achieve 5x the revenue increases from AI compared to others.
• They will achieve 3x the cost reductions from AI.
• But 60% of companies realize hardly any value at all.

Now, where that set of conclusions come from is quite a question! Skeptical goggles must be donned.

It’s hard for a scientist to parse the way through all the business babble that seems to be attached to consultants of this sort, but the main conclusion seems to be that the winners moved early, spent more, reinvested any gains, persisted over years, and had senior executive involvement.

I suspect there would be vigorous disagreement, at least on “senior executive involvement”, with the authors of the MIT study above, who found that bottom-up AI projects sometimes worked better than the top-down driven ones.

Surely there must be a deeper conclusion than “spend more, try harder”, but I couldn’t wade through the business speak to dig it out. The reports are written in a language that’s clearly not for scientists, or at least not this scientist. I found no math to justify the claims above of 5x revenue increases and 3x cost reductions.

Another quite deep business study comes from BBC’s analysis of how often AI summarization programs misrepresent news. ^[8] They worked with another organization, the European Broadcasting Union. Obviously, as a news source, they are quite concerned whether their work is being misrepresented to people.

Their conclusion, immediately stated, is stark (emphasis added):

New research coordinated by the European Broadcasting Union (EBU) and led by the BBC has found that AI assistants – already a daily information gateway for millions of people – routinely misrepresent news content no matter which language, territory, or AI platform is tested.

The intensive international study of unprecedented scope and scale was launched at the EBU News Assembly, in Naples. Involving 22 public service media (PSM) organizations in 18 countries working in 14 languages, it identified multiple systemic issues across four leading AI tools.

Their key findings are rather grim:

Key findings:

• 45% of all AI answers had at least one significant issue.
• 31% of responses showed serious sourcing problems – missing, misleading, or incorrect attributions.
• 20% contained major accuracy issues, including hallucinated details and outdated information.
• Gemini performed worst with significant issues in 76% of responses, more than double the other assistants, largely due to its poor sourcing performance.
• Comparison between the BBC’s results earlier this year and this study show some improvements but still high levels of errors.

Their response was to make a “News Integrity in AI Assistants Toolkit”, which appears to be a list of questions to ask about flaws that AI assistants might have injected into their summaries that providers should work to eliminate, and criteria to build media literacy about them.

Media literacy is great, but we’ve utterly failed to build it thus far. So color me “pessimistic” here.

Again, think about this carefully:

• Would you hire an employee assistant to write you summaries, if they materially lied and misrepresented 45% of the time?
• If not, why bother with an AI assistant which is well-documented to do so?

A Look Behind the Corporate Curtain

If the benefits are so marginal and so costly, we have to ask why there is so much hype around corporate use of AI. Some of it, of course, can be explained by the fact that the AI companies providing it will crash under their highly leveraged debt if they don’t succeed, so they talk about it constantly. But why the demand side?

Fortune has a summary of a 2026-Jan-07 study from Oxford Economics ^[9] that offers a rather more cynical answer (emphasis added):

In a January 7 report, the research firm argued that, while anecdotal evidence of job displacement exists, the macroeconomic data does not support the idea of a structural shift in employment caused by automation. Instead, it points to a more cynical corporate strategy: “We suspect some firms are trying to dress up layoffs as a good news story rather than bad news, such as past over-hiring.”

Spinning the narrative

The primary motivation for this rebranding of job cuts appears to be investor relations. The report notes that attributing staff reductions to AI adoption “conveys a more positive message to investors” than admitting to traditional business failures, such as weak consumer demand or “excessive hiring in the past.” By framing layoffs as a technological pivot, companies can present themselves as forward-thinking innovators rather than businesses struggling with cyclical downturns.

Oxford Economics suggests a test: if AI is replacing humans at scale, then the productivity per worker for the remaining workers should be shooting up. It is not; productivity growth is in fact decelerating.

In other words: historical behavior of management suggests, and the data confirm, that the main use of AI might be to camouflage layoffs. They’re hungry to fire people, and saying it’s because they “hope AI will replace” some workers makes them sound smart, rather than that they over-hired in the past.

Your humble Weekend Editor has had many years of generally unpleasant close-range observation of management. This theory checks out.

A Tempting Response

This is enough to frustrate web site owners: the AI crawlers come frequently, consume enormous resources downloading content, and using it without permission to make crappy LLMs. The original owner may incur hosting fees to keep serving his content at scale to crawlers who use it in AI training without permission.

People have thought about this a lot, and one popular solution is a software package called iocaine. ^[10]

Upon detecting an AI crawler, it quickly and cheaply generates endless pages of nonsense to feed to the crawler until it gives up. These pages, it is hoped, will eventually poison the training data for the AI on whose behalf the crawler is running.

The name comes from the “colorless, odorless, tasteless poison” in the movie The Princess Bride. The character of the incompetent Vizzini, played by actor Wallace Shawn shown here, thinks himself a genius. Like Trump, for all his flowery self-praise, he is incompetent and ends up poisoning himself in a “battle of wits” over the poison iocaine.

As satire, it’s hilarious. Now that we’re living with an entire US government full of Vizzini-like figures, We Are Not Amused.

(Alas, on this CLBTNR we have insufficient control over the servers to run iocaine. Really, we ought to move to Codeberg & Codeberg Pages, to get out of the US anyway. But that still wouldn’t offer us enough server control for iocaine. But it would prevent mischief from US big tech companies that run everything now. That’s a thought for another day.)

The Weekend Conclusion

With such low success rates, say around 5%, we have to ask whether success of corporate AI LLMs is due solely to chance, not skill. I don’t know the answer to that, which is disturbing: if they were that productive, the answer should be blatantly obvious!

I’m reluctantly giving the nod to Oxford Economics in their suggestion that the main corporate use of AI for now is to make layoffs/low hiring look smarter to than they really are.

Generative AIs via the Large Language Models are unfit for any purpose.

(No, no; you are mistaken: any purpose!)

(Ceterum censeo, Trump incarcerandam esse.)

Addendum 2026-Jan-22: Price Waterhouse Coopers Agrees

The auditing, tax, and business consulting firm Price Waterhouse Coopers recently released their 29th annual global CEO survey. ^[11] They are in substantial agreement with the above reports from MIT, CMU, Boston Consulting Group, The Economist, the BBC, and Oxford Economics: AI LLMs provide little to no benefit in corporate deployments.

A survey of 4,454 business leaders says no increase in revenue and no decrease in costs, despite massive investment in AI LLMs:

• 12% saw both increased revenue and lowered costs, but …
• 56% saw neither benefit!

About one-third of CEOs (30%) say their company has realised tangible results from AI adoption over the last 12 months through additional revenues. On the question of costs, 26% of CEOs say costs have decreased due to AI, while 22% report an increase. More than half (56%) say their company has seen neither higher revenues nor lower costs from AI, while only one in eight (12%) report both of these positive impacts.

Sadly, PwC seems to have drunk the Kool-Aid: they recommend investing even more in AI LLMs, and transforming corporate culture to use it everywhere, rather than in tactical pilot projects. That seems like a very peculiar position for a storied accounting firm with a focus on the profit/loss numbers… which are unfavorable to LLM usage in business.

Disinformation is, indeed, a powerful drug.

Notes & References

1: J Scalzi, “‘AI’: A Dedicated Fact-Failing Machine, or, Yet Another Reason Not to Trust It For Anything”, Whatever blog, 2025-Dec-13. ↩

2: D Seetharaman, S Mukherjee, & K Hu, “AI promised a revolution. Companies are still waiting.”, Reuters, 2025-Dec-16. ↩

3: C Doctorow, “AI can’t do your job”, Medium, 2025-Mar-18. ↩

4: Economist Staff, “Investors expect AI use to soar. That’s not happening”, The Economist, 2025-Nov-26. ↩

5: S Estrada, “MIT report: 95% of generative AI pilots at companies are failing”, Fortune, 2025-Aug-18.

The study to which they refer is:

A Challapally, et al., “The GeneAI Divide: State of AI in Business 2025”, MIT NANDA (“Networked AI Agents in Decentralized Architecture”), 2025-Jul. ↩

6: B Spice, “Simulated Company Shows Most AI Agents Flunk the Job”, Carnegie-Mellon CS Dept News, 2025-Jun-17.

The paper on which they’re reporting is:

FF Xu, et al., “TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks”, arχiv 2412.14161, submitted 2024-Dec-18, last revised 2025-Sep-10. DOI: 10.48550/arXiv.2412.14161.↩

7: J Apotheker, et al., “The Widening AI Value Gap”, Boston Consulting Group, 2025-Sep-30.

The study to which they refer is:

J Apotheker, et al., “The Widening AI Value Gap: Build for the Future 2025”, Boston Consulting Group media publications, 2025-Sep. ↩

8: BBC Media Centre Staff, “Largest study of its kind shows AI assistants misrepresent news content 45% of the time – regardless of language or territory”, BBC Media Centre, 2025-Oct-22.

The study to which they refer is:

European Broadcasting Union (EBU) Staff, “News Integrity in AI Assistants: An international PSM study”, BBC Media Centre, 2025-Oct.

The toolkit to which they refer is:

EBU Staff, “News Integrity in AI Assistants: TOOLKIT”, BBC Media Centre, 2025-Oct. ↩

9: N Lichtenberg, “AI layoffs are looking more and more like corporate fiction that’s masking a darker reality, Oxford Economics suggests”, Fortune, 2026-Jan-07. ↩

10: Madhouse Projects Staff, “Iocaine: The deadliest poison known to AI”, Iocaine Web site, downloaded 2026-Jan-09. ↩

11: PwC Staff, “PwC’s 29th Global CEO Survey: Leading through uncertainty in the age of AI”, Price Waterhouse Coopers 29th Global CEO Survey, 2026-Jan19. ↩

The Backgrounder

Let’s start with the very, very bad results that vaccine disinformation is having, all the way down to the doctor-patient relationship. This stuff is just plain, pure, evil.

Since you probably don’t want to take my word for it, consider Dr. Krutika Kuppalli, writing recently in STAT News. ^[1] She is an infectious diseases physician, whose work focuses on emerging infectious diseases, outbreak response, vaccine policy, and clinical care of complex infections. She knows a thing or two about both diseases & vaccines, and also about how to make the right thing happen in patient care.

She compares caring for patients now to something like a war zone:

I have spent my career caring for people facing some of the world’s most dangerous infectious diseases — Ebola, mpox, Covid-19. I have worked in outbreak zones, in understaffed hospitals, in field units built out of necessity. I’ve seen firsthand how vaccines transform the trajectory of a disease, a community, and a country.

But nothing has prepared me for the exam room conversations I’m having now.

Over the past few years, the rise of anti-science and anti-vaccine rhetoric has fundamentally changed the relationship between clinicians and patients. It has made routine preventive care feel like walking into an ideological minefield. Increasingly, it is making it harder and sometimes nearly impossible to protect patients’ health.

Whenever the concept of life-saving vaccinations come up, she can see some of her patients tense up, or shut down listening. She says it’s as though they’re thinking, “I don’t believe anything you’re about to say”. Needless to say, this least to poor decision making on the patient’s part. Often enough, fatally poor.

This puts a burden on the caregivers:

The emotional toll is profound — moral injury from trying to protect patients but being unable to break through the disinformation shaping their choices, burnout from debating the facts repeatedly, and sadness from watching preventable illnesses occur.

Kuppalli uses the term “moral injury”, a concept as profound as it is regrettably useful now to explain why we all feel terrible all the time: we are forced into being complicit with terrible things, under our anti-science authoritarian rulers. We all want to follow what might as well be the Zeroth Commandment: Don’t Do Terrible Things. But we are caught up in the tidal waves of evil driving us upon the rocks of Terrible Things.

It gets even more tragic when you consider RFKJr’s manipulation of the CDC into withdrawing advice for pregnant people to get the COVID-19 vaccine. ^[2]

Early on in the pandemic, under Biden, the CDC determined that having COVID-19 while pregnant would not only increase risks of autism and other birth defects, but also the potential mothers faced a 70% increase in mortality. The decision was easy, and may even have been taken too slowly & cautiously: get vaccinated, get a bigger chance to live, and get a lower chance of birth defects like autism.

But then: Kennedy fired all 17 members of the ACIP (Advisory Committee on Immunization Practice), installed some deeply unqualified replacements, and removed the recommendation for vaccinating pregnant people.

This goes against all scientific evidence and medical practice, according to professional organizations like the Society for Maternal-Fetal Medicine and the American College of Obstetricians and Gynecologists.

A Harvard Med School study of births between 2020-March and 2021-May (before vaccine availability) showed neurodevelopmental diagnoses in 16.3% of babies exposed to COVID-19 in utero vs 9.7% of babies not so exposed, a statistically significant hazard ratio. It was even worse if the COVID-19 exposure happened in the 3rd trimester, especially for boys.

And yet… right-wing disinformation grinds on, telling people to endanger themselves and their babies.

Mortality (Non-)Risk and the COVID-19 Vaccine

With those stern reminders of the deadly serious impact of vaccine disinformation campaigns, let’s look at 4 papers on the actual, measurable risks.

A Mathematical Digression: Poisson Regression & Adjusted Incidence Rate Ratios

First, a little mathematical digression.

It occurred to me that for most people it’s not obvious why Poisson regression is a useful tool for calculating adjusted Incidence Rate Ratios (IRRs). So let’s fix that! (The Wikipedia page on Poisson regression is a good starting point.)

Poisson regression tries to predict a count of events $Y$ (e.g., number of medical adverse events) from a vector of features $\mathbf{x}$ (e.g., age, vaccination status, risk status). Predicting the log mean of $Y$ conditional on $\mathbf{x}$ with regression coefficients $\alpha$ and $\beta$:

This would fit your observed values of $Y$, but adjust them a bit so they make sense as groups with the covariates $\mathbf{x}$.

Now if you want to compare 2 groups, with observed counts $Y_1$ and $Y_2$ with group covariates $\mathbf{x}_1$ and $\mathbf{x}_2$ (say, vaccinated and unvaccinated people within the same age cohort), then you’d use the regression model like this:

Take the difference, and you get a log estimator (almost) for the ratio:

So this plus the uncertainty estimates on $\beta$ from the regression get you an estimator on the ratio and 95% confidence limits.

A couple caveats:

• Yes, this depends on the coding levels for $\mathbf{x}$. But if you have 2 groups, say vaccinated and unvaccinated, coded as 0 and 1, then $\mathbf{x}_1 - \mathbf{x}_2 = 1$, conveniently enough.
• Yes, the ratio of the expectation values is not the expectation of the ratio. Ratio statistics is a whole ‘nother thing. See, for example, our method on a method of Gauss hypergeometric functions for ratios of Beta-distributed variables to get some idea how hairy that gets. The Poisson method used here is apparently good enough, often enough, that it’s widely used.
• The variables being predicted are not actually counts, but rates. That is, there’s some kind of normalization done for each covariate group, e.g., divide by the number of fully vaccinated 18-44 year olds to get an incidence rate, say, per 100k person-years. That mildly complicates things, but is intellectually straightforward.

In the end you get (almost) an estimator for the incidence rate ratio, adjusted for the covariates, and a 95% confidence interval on it.

(I’d have done it differently using my method of ratio statistics on Beta-distributed event probabilities, but I admit that’s a niche taste.)

Study 1: Revisiting Dahl, et al. on All-Cause Mortality in Norway

This Crummy Little Blog That Nobody Reads (CLBTNR) does’t have wide readership. But I know there are a few of you who are incorrigible long-term readers, and thus might remember when we blogged about this paper back in September. We’re going to repeat that material here, both to have all the analyses in one place and just in case an innocent new reader might stumble by. (Hey, it could happen?)

As we wrote back in September:

We definitely see increased all-cause mortality rates at the onset of the pandemic. Were these due to the vaccines, or due to COVID-19 itself (and its disruption of health care in general)?

For that, we turn to a 3-year study by Dahl, et al. ^[3], who looked at all-cause mortality in a broad population in Norway (universal health care!), over 2021-2023 (3 years).

Note that this is a preprint, which is not as yet peer-reviewed. So… grain of salt.

First, let’s look at their study cohort, the summary table of which is shown here (click to embiggen).

• It was a retrospective cohort study, including just about everybody over age 18 living in Norway in the years 2021-2023.
  • They were able to mine real-time national health registry data to obtain a study cohort of 4,645,910 people.
  • The 2024 population of Norway is around 5.5 million, so this was nearly the entire country in 2021-2023.
  • Subjects were categorized as unvaccinated, partially vaccinated (1 or 2 doses), and fully vaccinated (3+ doses).
    • People changed vaccination groups upon receiving a new dose. This was reported in real time by the national electronic medical records system.
    • These are obviously not the JN.1/LP.8.1 vaccines of this year, but rather the mRNA vaccines first available in 2021 and their modified versions through 2023.
    • If you want to study long-term effects, you have to look long term, which means including older treatments like the very first mRNA vaccines. Yes, mRNA vaccines have been in use for long enough that we can look at the first versions as having been “in the old days” of 2021!
• Death outcomes were from the National Population Register.

Now let’s consider their calculations. They stratified by analyzing each age group separately. Within each age group, they performed Poisson regressions to adjust for covariates like gender, place of residence, and by whether they were in a high-risk group.

These Poisson regressions yielded an adjusted incidence rate ratio of all-cause mortality, for each vaccination group compared to the unvaccinated. This looks almost exactly like the method of the previous paper, except that instead of measuring 29 adverse events for a few months, they measured only all-causes mortality for 3 years.

The results are shown here, in a forest plot (click to embiggen).

• There are 4 groups, each in a horizontal strip. The most important one is the top strip, which represents all 3 years combined.
• Within each such group, they first stratify by vaccination status (unvaccinated, partial, and full) and then by age group (18-44, 45-64, and 65+).
• NB: Since the unvaccinated group is the baseline for comparison, the ratio for them is always exactly 1. We’re interested in whether the vaccinated groups show a ratio less than 1 (fewer deaths) or greater than 1 (more deaths).

Note that the adjusted IRR is always less than 1, and is in fact bounded below 1 by its 95% confidence interval! Also note that in the 3-year combined dataset, the 95% confidence intervals are very tight: a consequence of having 4.6 million test subjects! Universal health care is good for health care, but it’s also great for research.

(You might be curious about the one weird apparent exception for fully vaccinated, age 18-44, in 2021 only: the 95% confidence interval crosses 1. If you look at the number of deaths in that vax group and age group for that year, there were only 13! Basically this group was so well protected from dying that there were too few deaths to estimate accurately the 95% confidence interval! That was a very safe time to be a fully vaccinated young Norwegian.)

Conclusion: The vaccinated population had a lower death rate from all causes.

Study 2: Semenzato, et al. on All-Cause Mortality in France

Thomas Aquinas is alleged to have said, “Homo unius libri timeo” (I fear the man of one book). It’s slightly unclear – at least to me – whether he meant he feared arguing with someone who was deeply specialized in one area, or whether he was just tired of arguing with semi-educated people who hadn’t the depth of having read many books.

If we let the classical allusion go either way, in science we should always fear the person of just one study: an effect really has to replicate before we take it completely seriously.

And so it is here: now comes a study from Semenzato, et al. ^[4], telling us if Dahl, et al. above in Norway can be replicated in France.

Like Dahl, this study is only possible because of universal healthcare and uniform electronic medical records. It used a great fraction of the population of France. Needless to say, the study is more than adequately powered.

They studied all causes of mortality for 4 years post-vaccination, in people ages 18-59. As shown by their CONSORT flowchart of patient selection shown here (their figure e2, in the supplement; click to embiggen), they started with a staggering 33,869,603 people from the French electronic medical records who were (a) aged 18-59 and (b) alive on 2021-Nov-01. After dividing them into vaccinated and unvaccinated groups and filtering for this-n-that as shown, they were left with 22,767,546 vaccinated and 5,932,433 unvaccinated subjects. Note here the influence of French medicine, having encouraged the vast majority of people to get vaccinated! This was not a crossover design, i.e., they filtered out unvaccinated people who chose to get vaccinated at various points.

These individuals were followed for 4 years: again, like Dahl, a giant study with long follow-ups to detect any long-term mortality effects. You simply cannot argue they didn’t look hard enough!

Again like Dahl, they did some statistical adjustments within each group, adjusting the morbidity count. For example, the vaccinated group tended to be older, more female, and less poor, so the results have to be adjusted for that. They adjusted for:

• Various sociodemographic factors like age stratified into 4 groups, economic class, place of residence, and level of medical insurance supplements to the state health insurance.
• 41 different comorbidities of various sorts: cardiometabolic, respiratory, cancer, inflammatory and other problems, as well as obesity, smoking, and alcohol disorders.

Slightly unlike Dahl, instead of Poisson regressions they did Cox regressions, which properly account for “censorship” when you lose track of a subject. This is, if anything, an improvement over Dahl.

At that point they computed a hazard ratio: there’s a lot of nuance to what that means, but basically it amounts to a sophisticated measure of mortality risk in vaccinated people divided by unvaccinated people. Less than 1 means less risk for vaccinated folk. A variety of sophisticated methods get you not just the hazard ratio, but a 95% confidence interval.

Here are their results, showing a “forest plot”, i.e., the hazard ratios and their confidence intervals overall and for numerous subgroups (click to embiggen).

Note that in all cases, the hazard ratio was less than 1, i.e., vaccinated people were safer overall and in every subgroup. Not only was the median hazard ratio below 1, but the entire 95% confidence limit was as well, conveying a good deal of statistical significance strength to the conclusion that vaccinations were safer than not. (The lone almost exception is Corse, i.e., residents of Corsica. Even there, the mean was less than 1, just the tip of the upper limit of the 95% confidence interval says a very, very weak “maybe”. There’s probably something about localized poverty or access to medical care in Corsica going on there, would be my guess.)

Allow me to brute-force the summary for those of you who don’t like diving into hazard ratios. After following millions of patients for 4 years:

• The vaccinated group was 25% less likely to die from any cause than the unvaccinated group.
• If you focus on COVID-19 in particular, the vaccinated group was 75% less likely to die in a hospital from COVID-19 than the unvaccinated group.
• The vaccinated group is still less likely to die even when you remove the COVID-19 deaths (thereby giving an unfair advantage to the unvaccinated group, but not enough to overcome the difference; being vaccinated is still safer).

As you can see from the forest plot above, this was very consistent across subgroups, or, as the authors put it:

Results were consistent when stratified by age, sex, region, CSS coverage, social deprivation index, history of COVID-19, and history of chronic disease as well as when excluding individuals in the unvaccinated group who were vaccinated during follow-up.

Conclusion: Like the Dahl study, the Semenzato study tells us the vaccinated population had a lower death rate from all causes and that this was robust across all subgroups.

Study 3: Andersson, et al. of JN.1-Updated mRNA Vaccine Safety

One thing I’ve learned over the past 5 years is that people infected by vaccine disinformation are nothing if not persistent, sometimes fatally so. They might, for example, conclude: “Yeah, those old vaccines might have been ok, but the new ones updated for this year have got to be deadly.”

Right. With something of a heavy sigh, let’s address that.

Andersson, et al. ^[5] have done a study on the safety of the latest version of the mRNA vaccines, updated for the JN.1 strain of SARS-CoV2.

This is, again, one of those lovely European studies made possible only with universal healthcare and uniform electronic medical records: their study population was more or less the entire population of Denmark. (However, with a new version of the vaccine only recently available, this has to be a short-term study: from 2024-May-01 to 2025-Mar-31.) So over a period of roughly 1 year, they did 28-day post-vaccination follow-ups on a cohort of:

• 1,585,883 subjects total,
• 1,012,400 of whom got updated mRNA COVID-19 shots optimized for the JN.1 lineage, and
• the rest who did not get such an update.

So again, they’re statistically powered enough to go hunt bears. Angry bears.

They looked at 29 kinds of medical adverse events such as anaphylaxis, ischemic cardiac events, cerebrovascular events, arterial thromboembolism, and many more. All of those were carefully limited to the criteria described in the ICD-10 disease codes, for objectivity.

As in the previous 2 papers, of course they calculated a hazard ratio and its 95% confidence interval. A particular medical adverse event was considered statistically significant only if the hazard ratio and its 95% whiskers were all above 1 (more risk) or below 1 (less risk). The observation was for a period of 28 days after vaccination for the vaccinated population; I don’t know exactly what they did for the unvaccinated.

• As you can see from the by-now familiar forest plot shown here (click to embiggen), most adverse events (rows in the table) have a hazard ratio that is statistically indistinguishable from 1: i.e., there is no increase in risk.
• There are, however, many cases where the box and its whiskers are below 1, i.e., a statistically significant decrease in risk. Among them are ischemic cardiac event, cerebrovascular event, cerebrovascular infarction, deep venous thrombosis, pulmonary embolism, pericarditis, coagulative disorders, heart failure, acute kidney failure, and acute pancreatitis.

Conclusion:

• In the 28 days after receiving the JN.1 updated mRNA COVID-19 vaccine, there was no statistically significant increase in risk in any of 29 medical adverse events studied.
• However, in 10 of those events, the risk appears to have been statistically significantly lowered.

Study 4: Grippin, et al. on Cancer Reduction via mRNA Vaccines

Finally, let’s look at another bit of good news about vaccines.

In the waning days of my career before retirement, I worked a lot with people doing immunotherapy research in oncology. Basically, those are various sorts of attempts to get your immune system to attack the cancer, without attacking normal tissues. That’s always the game: kill the tumor, not the patient. The immune system has about a billion years of experience in making fine distinctions about which cells to kill, so when this works it works really well.

COVID-19 vaccines mess with the immune system. That’s for the better, in terms of not getting COVID-19, but does it affect the response to cancer immunotherapies?

Yes, it does make response to at least one cancer immunotherapy better, according to a paper by Grippin, et al. ^[6]

There’s a type of cancer immunotherapy called an immune checkpoint inhibitor (ICI). Now, there are volumes of things to know about those, but the crude summary is: immune checkpoint molecules stop the immune system from overreacting, so ICI therapy blocks those checkpoints, allowing the immune system to proceed. It’s sort of like taking your foot off the brakes of the immune system, and letting it race ahead. That’s not a great idea in normal circumstances, but if it’s fighting a cancer then the trade-offs are in favor of an immune system that attacks your cancer.

Unfortunately, if your immune system is not especially active, then blocking the checkpoints won’t do much.

One response to this has been “cancer vaccines”, where we make a vaccine special for you, attuned to your particular cancer’s mutations and weird proteins it expresses on the surface of its cells. Needless to say, that’s expensive, complex, and difficult.

Grippin, et al.’s striking result is that mRNA COVID-19 vaccines have a similar result: they stimulate your immune system enough that it responds better to ICI therapy against your cancer.

There’s a lot of interesting stuff to know about how that happens, with things like CD8+ T cells, PD-L1 expression, various interferons, and so on. And it turns out the response has nothing much to do with SARS-CoV2, but a lot to do with the way mRNA vaccines and their lipid nanoparticle (LNP) vehicles strongly stimulate the immune system. (Non-mRNA vaccines do not have this effect; it has to be mRNA + LNPs.) However, the biological details of the mechanism of action are something we’ll leave to the biologists for now. Instead, we’ll just skip to the summary effect, of whether it improves cancer survival.

Here you see a collection of what are called Kaplan-Meier curves, for non-small cell lung cancer (NSCLC; top 3 plots) and melanoma (skin cancer; bottom 2 plots) (click to embiggen).

• The horizontal axis is time since start of treatment.
• The vertical axis is the probability of survival (OS, or “overall survival”). The curves go down as people start to die. You’d like them to stop going down, or at least do down more slowly!
  • The blue curves are for patients who got ICI + a recent mRNA COVID-19 vaccine booster.
  • The red curves are for patients who got only ICI.
• There are some interesting computations that can be done here with Cox regression to get a hazard ratio and a logrank $p$-value.
  • That $p$-value shows how statistically significant the difference in the curves is; lower is better.
  • In each case, the $p$-value shown in the lower left of each plot is below 5%, showing the difference between the red and blue curves is significant, i.e., a real thing likely to reproduce in the future.

You pretty much want to be a patient on the upper curves – the blue curves combining mRNA/NLP vaccines + ICI – because they live longer.

The really startling news here is that the patients who got the mRNA vaccine + ICI combination therapy always did better, and that the result is statistically significant.

Conclusion: mRNA + LNP vaccines prime the immune system so it’s more responsive to immune checkpoint inhibitors in cancer therapy.

If I had a cancer and my oncs wanted to give me immunotherapy of just about any kind, I’d wave this paper in their faces and demand an mRNA COVID-19 vaccine booster immediately.

The Weekend Conclusion

The evidence is starting to pile up:

• The entire nation of Norway (Dahl, et al.) says that there is a remarkable decrease in all-cause mortality among people who got COVID-19 vaccinations.
• The entire nation of France (Semenzato, et al.) says that there is also a remarkable decrease in all-cause mortality. And decrease in hospitalizations. And decrease in all mortalities even if you subtract out the COVID-19 deaths.
• The entire nation of Denmark (Andersson, et al.) says there is no short-term increase in 29 medical adverse effects within a month of the very latest JN.1 vaccine. In fact, in 10/29 adverse effects studied, the vaccine is protective.
• In a study of immune checkpoint inhibitors in non-small-cell lung cancer and melanoma, an mRNA + lipid nanoparticle not only improves response in a variety of ways, it makes patients live longer.

Don’t tell me any more that you think mRNA vaccines increase long-term all-cause mortality. You’re just ignoring the truth, at this point.

Though, alas, I do not expect this will change any minds of anti-vaxers. Disinformation is a powerful drug.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: K Kuppalli, “Rise of anti-science rhetoric has fundamentally changed the relationship between doctors and patients”, STAT News, 2025-Dec-10. ↩

2: D Eldeib, “Amid Confusing CDC Guidance About Vaccines, Study Highlights New Risk of COVID-19 During Pregnancy”, Pro Publica, 2025-Nov-26. ↩

3: J Dahl, et al., “COVID-19 mRNA-vaccination and all-cause mortality in the adult population in Norway during 2021-2023: a population-based cohort study”, medRχiv, 2024-Dec-16. DOI: 10.1101/2024.12.15.24319058.

NB: This is an as yet not peer-reviewed preprint. ↩

4: L Semenzato, et al., “COVID-19 mRNA Vaccination and 4-Year All-Cause Mortality Among Adults Aged 18 to 59 Years in France”, JAMA Network Open 8:12, 2025-Dec-04. DOI: 10.1001/jamanetworkopen.2025.46822. ↩

5: NW Andersson, et al., “Safety of JN.1-Updated mRNA COVID-19 Vaccines”, JAMA Network Open, 8:7, 2025-Jul-28. DOI: 10.1001/jamanetworkopen.2025.23557. ↩

6: AJ Grippin, et al., “SARS-CoV-2 mRNA vaccines sensitize tumours to immune checkpoint blockade”, Nature 647, pp. 488-497, 2025-Nov-13. DOI: 10.1038/s41586-025-09655-y. ↩

Vanguard’s New Portfolio Recommendation

This summer, Forbes landed an interview with Vanguard’s chief investment officer, Greg Davis. ^[1] This is a measure of how seriously Vanguard takes this information: one does not get an interview with such an important person easily, so Vanguard must really want to get the news out. (Though, strangely, Forbes spent a paragraph describing how Davis was dressed, as if that meant something. I will never understand why reporters are just obsessed about The Narrative, trying to make everything about the personalities of people with power.)

They’re lowering the percentage of US stocks they recommend in portfolios for a pretty straightforward reason: stocks are expensive, as measured by P/E ratio or the even better Shiller CAPE (cyclically averaged P/E ratio, also adjusted for inflation).

• The P/E ratio of a stock, or better yet and index, is the price to earnings ratio. Divide the price of a stock by the trailing 12 months of earnings (or your estimated earnings going forward, if you’re daring).

  This tells you how much you’re paying to buy the earnings of the business. A high P/E ratio (say, 20-30) means the stock is expensive compared to its earnings. This might be because investors think there’s a lot of growth possible, and that future earnings will be even higher. But… still expensive.

• The Shiller CAPE, or Cyclically Adjusted P/E ratio, attempts to account for inflation and for the business cycle.

  It looks back 10 years, inflation-adjusting all the earnings and averaging them. The 10 year lookback means you’re asking about the performance of the stock over (usually) an entire business cycle.

  With the 10 year lookback, CAPE is more data hungry than the simpler P/E ratio, which makes Wall St types impatient with it.

Davis says Vanguard’s models predict the next decade will average about 1/3 of the returns in the previous decade:

“Our investment strategy group’s projection is that U.S. equity market returns are going to be much more muted in the future,” Davis warns. “Over the past ten years, the S&P returned an average of 12.4% annually. We’re predicting the figure to drop to between 3.8% and 5.8% (midpoint of 4.8%) over the next decade.”

Is the high CAPE ratio a reasonable concern?

It appears so.

Finance professor Michael Finke did a study ^[2] which was picked up by John Rekenthaler at Morningstar a few years ago.^[3] Rekenthaler, showing admirable skepticism, redid Finke’s regression using the inflation-adjusted CAPE and inflation-adjusted stock market returns data from Morningstar’s own databases.

As you can see from the plot, the fit is excellent. Finke reports an $R^2 \sim 90\%$ or better. That’s pretty astounding, given that it hasn’t really worked that well in previous periods.

As I write this, the US CAPE ratio (“Shiller PE”) stands at 40.30. Armed with that fact, look at the regression plot that predicts the next 10 years of inflation-adjusted stock returns being negative, and then tell me about your risk appetite for stocks!

Though, let’s be fair: if CAPE went from previously not working at predicting stocks to working now, nothing prevents it from going back to not working in the next decade. As Yogi Berra is alleged to have said, “Prediction is hard, especially when it’s about the future.”

So Davis says people who would normally have a 60/40 (60% stocks/40% bonds) portfolio should not only rebalance, but rebalance to 40/60, leaning hard into bonds. That’s… bold.

A couple weeks later, in August, Business Insider ran a similar article ^[4], claiming Vanguard said:

• Vanguard’s models forecast 3.3% - 5.3% annual stock returns, vs 4% - 5% for bonds over the next 10 years.
• People – like your humble Weekend Editor – who would normally prefer a 60/40 portfolio should move to a 30/70 portfolio.

So they ran the mighty Vanguard Capital Markets Model (VCMM) to estimate future returns and their uncertainties, and they ran the equally mighty Vanguard Asset Allocation Model (VAAM) to construct recommended portfolios. The image here shows the results, tagged as having come from a run on 2025-Jun-30. It compares a 60/40 benchmark portfolio (top) with their proposed 30/70 portfolio (bottom).

Now… the Fortune interview where they recommended 40/60 was published 2025-Jul-24, and this Business Insider article recommending 30/70 was published 2025-Aug-06. So it’s just 2 weeks later, and they’ve gotten quickly more defensive? Why is the recommendation changing so rapidly, by such a large amount, and to an extremely defensive position? Do they know something the rest of us don’t?

It could be that the picture darkened dramatically in the 2 weeks between these publications. But it also could be that the VCMM and VAAM are just very sensitive to the input conditions, and don’t produce stable outcomes. In the latter case, it’s important not to be too fixated on the precise numbers, but rather to look at the general scenario: very high CAPE valuations, reasonable returns on bonds, and therefore low equity risk premia. In that situation, it makes sense to tilt more toward bonds, though it’s debatable exactly how much.

So we decided to check at the original source ^[5], because getting information filtered through journalists obsessed with The Narrative is frustrating.

Here we see Vanguard’s updated portfolio, with data current as of 2025-Oct-31. (Compare the Business Insider reporting using a Vanguard model run of 2025-Jun-30.) They’ve gone back to a 40/60 recommendation, which is quite a bit less extreme than the scary 30/70 allocation.

Interestingly, there’s also some helpful information on suballocations, i.e., tilting the stocks toward value (away from high-P/E growth stocks), and small cap (away from the Magnificent 7 big tech stocks). I found that gratifying, because for many years I’ve been using Vanguard’s US small-cap value index fund and international small-cap fund for that exact purpose. Now even Vanguard is cautioning people not to lean too heavily on US large-cap growth stocks.

Also gratifying, for a quantitative old nerd like your humble Weekend Editor, is the inclusion of a table of portfolio characteristics. The table compares the 40/60 portfolio with the “benchmark” 60/40:

• On the second line, we see that the standard deviation of returns is about 1/3 less, which we would expect from a larger bond allocation.
• But on the first line, we see that the mean returns are within a few 10ths of a percent of each other (5.5% vs 5.2%) and slightly higher for the bond-heavy portfolio! So this is about earning roughly the same, just with far, far less volatility. I’m starting to like this plan!
• As risk measures, consider the 3rd & 4th lines:

  • The Sharpe ratio is the return beyond the risk-free rate, divided by the amount of risk:

    \[S = \frac{E[R] - R_f}{\sigma[R]}\]

    That means it measures the amount of additional return you get for each unit of risk you take. Higher is better.

    The 40/60 portfolio is at 0.33, while the 60/40 benchmark is at 0.18. So the 40/60 is a more efficient risk taker, getting more return for the risk it takes.

  • The max drawdown is how much the portfolio might go down, peak to trough. Closer to 0 is better. We see here the max drawdown is only about 1/3 of that for the 60/40 portfolio! Again, that’s to be expected with bonds, but it’s nice to see a projection of the protection.

• Finally, on the last line of the table, is the thing I always want to see in any statistical model: what’s the probability this will work? Without that, I always wonder if somebody just forgot, or if they’re hiding it. Vanguard says there’s a 47% chance the 40/60 portfolio will underperform the 60/40. Ok, it would be nice to see that lower.

  But, really: a null hypothesis would say that the portfolios are the same, and the probability of underperformance would be 50%. The fact that it’s 47% is very close to that, and says this is about volatility reduction, not return maximization!

So all of that looks pretty sensible to me.

One other thing to check, just to make sure we’ve nailed everything down tightly, is exactly what the VCMM projections of market returns were, and how they differ from other predictions by people who aren’t urging this much caution.

So we looked at Vanguard’s report on the VCMM run of 2025-Oct-31 ^[6] and what Morningstar’s financial analysts came up with ^[7] as a part of their recommendations on retirement withdrawal rates.

First consider Vanguard (click through on these charts to see them full-size):

• Method: Vanguard’s forecast is a sophisticated Monte Carlo simulation, done by people whom I think are some of the best available. It’s estimating annualized returns over the next 10 years.
• Stocks: The stock market return forecasts are in the blue bars at the top of their chart.
  • Note that most of them are in the range of 3% - 5%, no more.
  • US Large Growth is the most miserable sector.
  • Things are much brighter if you tilt toward value stocks, small stocks, and ex-US international stocks, which are not so over-priced. So tilting to small-cap and value stocks, and strongly tilting to outside the US makes perfect sense.
• Bonds: The bond market return forecasts are in the yellow bars at the bottom of their chart.
  • First, note that these bond returns are in every way comparable to the stock returns! If you could get returns comparable to stocks while not having to take stock-like risk, wouldn’t you accept that bargain?

  • Second, Vanguard tends to like total bond market funds, including corporates. Here at Château Weekend, we tend to like US Treasuries, TIPS, and foreign government bonds (with a currency hedge back to the dollar).

    As we’ve previously written here on this Crummy Little Blog That Nobody Reads (CLBTNR) ^[8], corporate bonds look like a Treasury bond with a small amount of stock market risk added. If you’re trying to diversify away from some stock risk, you can’t do that by adding more stock. Hence our choice of bonds will be a bit more restrictive than Vanguard’s (q.v.).

Now compare with Morningstar:

• Method: Morningstar is making a 30 year forecast, since they’re doing it for projecting retirement spending levels. They don’t quite say what they did, except to say it’s got a “top-down” portion from things like valuations and earnings growth rates and a “bottom-up” phase involving human input from their equity analysts. They’re a bit more traditional in that regard than Vanguard, for better or worse. (Mostly worse, I think, given that equity analysts can be crowd followers as much as anybody else. But it’s a point of comparison to Vanguard.)
• Stocks: Note that their forecasts for stock returns (30 years, vs Vanguard’s 10 years) are seriously higher, at 8% - 12%. That’s more of a “business as usual” forecast, not one that is aware of the high CAPE and the rampant political instability & corruption. Maybe they think in 30 years none of that will matter?
• Bonds: Morningstar’s bond predictions look to be pretty much in line with Vanguard’s.

• Safe withdrawal rates vs equity percent: You might think that if Morningstar analysts predict stocks would have such high returns, they’d recommend more stocks in their retirement portfolios, right?

  Not so: they figure out the withdrawal rates a portfolio will support, with 90% probability of not running out of money, as a function of stock percent. For a 30 year period, this maxes out for portfolios between 30% stock and 50% stock!

  It’s somewhat surprising that this result is so low, given their rather sunny forecast. But it’s just realistic: if you must sustain withdrawals for decades, then the volatility of a high stock portfolio tends to kill you. Or at least bar you from getting their 90% success rates.

So while Morningstar forecasts much higher stock returns than Vanguard, they both come out with similar portfolio recommendations for sustainability looking forward 10 years or 30 years.

Again, this makes perfect sense to me.

What We Did

As we’ve written previously on this CLBTNR about the Weekend Portfolio ^{[9] [10] [11]}, our neutral policy portfolio would be the good ol’ 60/40 stock/bond allocation. However, high valuations and catastrophic political destruction had forced us to get more conservative at a 50/50 stock/bond allocation. We even increased our ex-US stock and bond holdings.

Now, Vanguard and – in a different way – Morningstar have pushed me to think that this might not have been enough.

The question is, how much? We saw above that Vanguard’s allocation recommendations swung from 30/70 to 40/60 over just a couple weeks. So the important thing is to take the general advice that bonds have better prospects, and allocate a portfolio we can live with. I settled on 40% stocks, 60% bonds.

• Tax location: As you can see, the tax-free (Roth IRA) component has increased a bit. That’s because all the stuff likely to grow faster is in the Roth, with only bonds in the Trad IRA. Also, we’re continuing our campaign of doing annual partial Roth conversions, to get as much money put in the tax-free part of the portfolio before RMDs begin. That is, we’re diversifying the tax structure of the portfolio at the same time as the rest of this.
• Overall allocation: 40% stocks/60% bonds.
• US/International stock allocation: 40% US/60% international. This applies both to stocks in general and to REITs. It amounts to a moderate bias away from the US.
• US/International bond allocation: 50% US, equally between intermediate Treasuries and TIPS, and 50% international. The international bonds are mostly government bonds of developed nations, with a currency hedge back to the dollar, as Vanguard recommends.
• Tilts: We tilt fairly heavily away from US large-cap growth stocks, in favor of US small-cap value stocks, international small stocks, and REITs both US and international (another form of value stock, really).

I think that covers the bases:

• adjust the stock/bond ratio to be more in favor of bonds,
• tilt to small, value, and international stocks,
• keep the US bonds in intermediate term Treasuries and TIPS,
• have a large portion of international developed nation government bonds,
• continue to do partial Roth conversions to get a little more tax armor.

The Weekend Conclusion

Vanguard’s market forecasts are pretty dim, and bonds are offering pretty good competition with reasonable returns and less risk. The US CAPE ratio is currently quite high, at 40.30. Those 2 facts combine to lower the equity risk premium and lower the expectation of stock returns.

Tanking up on bonds just makes sense, particularly for a retiree who is in the capital preservation phase of life.

Look, I’m not saying it’s time to run for the hills and lay in a supply of food and water. And this extremely conservative (for me) portfolio is not the way I’d invest in normal times. But these are decidedly not normal times.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: S Tully, “The investment chief at $10 trillion giant Vanguard says it’s time to pivot away from U.S. stocks”, Fortune, 2025-Jul-24.

NB: The link here goes to an archival site, to avoid the regrettable paywall. ↩

2: M Finke, “The Remarkable Accuracy of CAPE as a Predictor of Returns”, Advisor Perspectives, 2020-Jul-20. ↩

3: J Rekenthaler, “Maybe There’s Something to the Shiller CAPE Ratio, After All”, Morningstar, 2020-Jul-27. ↩

4: W Edwards, “Stocks are roaring higher this year, but Vanguard says investors should stick 70% of their money into bonds”, Business Insider, 2025-Aug-06. ↩

5: Vanguard Staff, “Bonds remain in favor in time-varying model portfolio”, Vanguard web site, 2025-Dec-10. NB: This article is apparently updated periodically, so you should expect to have to look at the latest version. ↩

6: Vanguard Staff, “Vanguard Capital Markets Model® forecasts”, Vanguard web site, 2025-Dec-10. ↩

7: AC Arnott, C Benz, & J Kephart, “What’s a Safe Retirement Withdrawal Rate for 2026?”, Morningstar, 2025-Dec-03. ↩

8: Weekend Editor, “Stock Diversifiers: Treasury vs Corporate Bonds?”, Some Weekend Reading blog, 2021-Jun-07. ↩

9: Weekend Editor, “The Weekend Retirement Portfolio”, Some Weekend Reading blog, 2021-Jun-19. ↩

10: Weekend Editor, “A Weekend Retirement Portfolio for the Trump-Revenant Era”, Some Weekend Reading blog, 2025-Feb-10. ↩

11: Weekend Editor, “Some More Revisions to the Weekend Retirement Portfolio”, Some Weekend Reading blog, 2025-Jun-11. ↩

The Human Sacrifice Goes On… and On… and On…

Here on this Crummy Little Blog That Nobody Reads (CLBTNR), we’ve for some time been having… opinions about Ukraine. ^{[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15]}

As we’ve been saying for a couple years now, we’re tracking the Russian casualty figures provided by the Ukrainian Ministry of Defence:

We’ve been using the Ukrainian Ministry of Defence’s figures for Russian casualties. Of course, one could object that they are a biased source. But when we looked at other sources, they were kind of in the middle of the pack. Some sources were wildly inflated, while others had extremely hard to believe small numbers. (The latter were institutions that insisted on a very high standard of evidence, like geo-location, identities, photographs, and so on. This leads to a very severe under-count, so people usually take their estimates and apply a multiplier derived… somehow.) The Ukraine MoD says they count, every day. That might even be true. But they seem reasonably credible compared to others, and they are the ones on the spot. So we’ll take their figures.

Regrettably, it now appears the Russian casualty figures are above 1.2 million dead (and considerably more who are injured, many disabled for life):

(As you can see, the number of casualties is just a hair above 1.2 million on 2025-Dec-26. Judging by the rate, it would have hit 1.2 million on about 2025-Dec-24. I missed that – holiday preparations, you know. Since Musk has turned X/Twitter into a Nazi bar, I refuse to have an account there and can’t look back far enough to see. But this is close enough!)

The hole being blown in the middle of the Russian demographic of 18-44 year old males, i.e., those more or less qualified for military service, continues to be enlarged. By our reckoning:

So 1.2 million dead is about $100\% \times 1.2\ \mbox{million} / 24\ \mbox{million} = 5\%$ of the military-age male population.

The Russian emigration and COVID-19 deaths (see previous post ^[15]: 900,000 men of military age emigrated and about 67,000 dead of COVID-19), we get about an extra million, for a total loss of 2.2 million. That’s $100\% \times 2.2\ \mbox{million} / 24\ \mbox{million}$, for a total loss about 9.17% of the Russian men of military service age.

These are men who will never return to work in the Russian economy. Their children will either grow up without fathers or not exist at all. Many women in the middle demographic of Russia will face the impossibility of finding husbands. This is the sort of thing that starts revolutions. (Though in the case of Russia, one never knows: they’ve tolerated worse in the past, when it comes to authoritarianism and mass deaths.)

As always, Bertrand Russell never quite said these exact words, but it’s right on the mark:

“The mark of a civilized man is the capacity to read a column of numbers and weep.” – often attributed to Bertrand Russell, who said things like this if not exactly this, but would in any case almost certainly agree with the sentiment

At the last Ukraine update on this CLBTNR, we said something that just encapsulates all the venom and malevolence of Russian, US, and Israeli governments, along with the rise of right-wing racist parties in Europe:

When we look at the deaths in Russia’s invasion of Ukraine, the deaths in Israel’s invasion of Gaza, the wholesale dismantling of public health in the US in favor of superstition, summary military executions of people in boats in the Caribbean, and masked men kidnapping people from the streets of the US with no due process at all… it is arguable that we can no longer claim to be civilized. We are, perhaps, just clever barbarians?

We have allowed right-wing populism turn us into vicious, superstitious, and venomously racist savages. And somehow we have done this on a planet-wide basis.

I wish that didn’t seem so accurate.

Comparison Against Our Casualty Rate Model

Here’s the updated plot, with all the depressing news:

• Time is on the horizontal axis, for the first 100 days of the Russian invasion.
• Number of Russian soldiers reported dead by the Ukrainian Ministry of Defence is on the vertical axis.
• The blue points in the lower left are the initial training data, about 100ish days into the war. The resulting regression is the dotted line and the gray uncertainty intervals around it. Rather than rehash the $F$-statistic, let’s just say the linear fit is excellent.
• The red points in the center to upper right are new data, collected approximately every 100,000 increment in casualties.

Note that the new data points are all well above the initial regression line. Sometime around day 450 (2024-Apr-10), the Russian death rate went up by about 43%, from about 700/day to about 1000/day. Either:

• the Ukrainians got smarter or more efficient at killing Russians, or
• the Russians started human wave attacks that made cheap sacrifice of their newly recruited troops.

(Or both, which is actually the most likely conclusion, to my mind.)

The data is practically screaming for a segmented regression model with a hinge function, which is unbearably fancy-pants language for “a line with a kink”. Perhaps next time I’ll do that, but I’m just too discouraged now.

The Weekend Conclusion

I used to wonder when we would awaken to the malevolent insanity and depraved indifference of our times and our leaders.

I no longer wonder that. Now I wonder if we will ever awaken.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: Weekend Editor, “Another Grim Anniversary”, Some Weekend Reading blog, 2023-Mar-02. ↩

2: Weekend Editor, “Do the Ukrainian Reports of Russian Casualties Make Sense?”, Some Weekend Reading blog, 2023-Apr-15. ↩

3: Weekend Editor, “Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-01. ↩

4: Weekend Editor, “Updated Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-09. ↩

5: Weekend Editor, “Updated${}^3$: Ukrainian Estimates of Russian Casualties Hit 200k”, Some Weekend Reading blog, 2023-May-17. ↩

6: Weekend Editor, “Ukraine Invasion: 250k Russian Dead”, Some Weekend Reading blog, 2023-May-17. ↩

7: Weekend Editor, “Tacitus in Ukraine”, Some Weekend Reading blog, 2023-May-25. ↩

8: Weekend Editor, “Casualties in Ukraine: Grief Piles Higher & Deeper”, Some Weekend Reading blog, 2024-Apr-10. ↩

9: Weekend Editor, “Post-Memorial Day Thought: 500k Russian Dead in Ukraine “, Some Weekend Reading blog, 2024-May-31. ↩

10: Weekend Editor, “Ukraine: 600k Russian Dead”, Some Weekend Reading blog, 2024-Aug-27. ↩

11: Weekend Editor, “Ukraine War: 700k Russian Dead”, Some Weekend Reading blog, 2024-Nov-04. ↩

12: Weekend Editor, “Ukraine War: 800k Russian Dead”, Some Weekend Reading blog, 2025-Jan-08. ↩

13: Weekend Editor, “Ukraine War: 900k Russian Dead”, Some Weekend Reading blog, 2025-Mar-21. ↩

14: Weekend Editor, “Ukraine War: 1,000,000 Russian Dead?!”, Some Weekend Reading blog, 2025-Jun-12. ↩

15: Weekend Editor, “Ukraine War: 1,100,000 Russian Dead”, Some Weekend Reading blog, 2025-Sep-22. ↩

They Did What Now?

We’ve known for some time that they’re petty, racist, and stupid. But every day, there appears news showing that they’re still worse than we expect. And so it is today: the US Department of State has been ordered to change typefaces in all their documents. ^[1]

What could possibly have been the reason for that?

According to The Guardian, Biden’s Secretary of State, Anthony Blinken, ordered a switch to the Calibri typeface in 2023. Apparently there’s evidence that Calibri is more legible to people with certain visual impairments, and possibly to screen-reader software for the blind. Well… that was just too DEI for the Trumpers! So they are now demanding a switch back to Times New Roman. In a cable seen by The Guardian, they say:

To restore decorum and professionalism to the Department’s written work products and abolish yet another wasteful DEIA program, the Department is returning to Times New Roman as its standard typeface.
…
This formatting standard aligns with the President’s One Voice for America’s Foreign Relations directive, underscoring the Department’s responsibility to present a unified, professional voice in all communications,

Apparently sans-serif typefaces lack “decorum”, do not exude “professionalism”, and thinking that you might want to make your documents readable by the visually impaired is “another wasteful DEIA program”. They probably think it’s more manly, too.

Here you can see the difference, in an illustration helpfully provided by The Guardian. Calibri, a sans-serif typeface, is on the left. Time New Roman, a serif typeface, is on the right. The main differences are that the sans-serif font has uniform stroke weights, no serifs at the ends of the strokes, and is in several places a bit “pointier”.

Now, if instead of banning Calibri they had banned Comic Sans, I could have given them a break. Typeface aficionados love to hate Comic Sans, but of course in my position as resident barbarian I don’t mind it. That sort of over-refined taste is like audiophiles who claim to hear differences in music only when they use Very Expensive Cables: pretty clearly self-delusion, but largely harmless beyond wasting money.

But this is something much worse: the mere fact that the switch to Calibri was made for readability for vision-impaired people was enough to give it the stink of disability and hence subject to DEIA witch-hunting. Like witch-hunting, they’re pursuing something that fundamentally doesn’t even exist, but Trumpers have long had impaired reality testing.

Also, it relates in a spooky way to something we previously wrote about on this Crummy Little Blog That Nobody Reads (CLBTNR), about right-wing bias in training LLM AI models. ^[2] In “Fit #4” of that post, we looked at right-wing bias of LLM AIs trained on a large corpus of old newspapers. You’d think that training on substantially everything would remove viewpoint bias, but…

• Right-wing newspapers have always been the preference of the rich.
• Hence, right-wing newspapers had more money to work with. This meant that:

  • They could print on higher-quality paper that was more likely to be preserved.

    Thus there’s a right-wing selection bias even if you scan “everything”.

  • They could afford to buy/license typefaces that might have improved legibility compared to the free alternatives of the day. Since everybody wants to be mistaken for a member of the upper class, we’ve spent a lot of time with those typefaces, making them more recognizable by OCR software that scans them in comparison to the fonts used by more pedestrian publications.

    Thus there’s a right-wing bias in what text is generated by the OCR, upon which the LLM AIs are trained.

Add that to the unexamined right-wing political bias of what’s “worth preserving”, and you end up with quite a bias indeed toward the viewpoints of the wealthy and the conservative, even where it seemed impossible for such bias to exist.

Interesting fact: the Times New Roman typeface was created for The Times of London, quintessentially a conservative British newspaper. In modern times, this has made it quintessentially the conservative choice. I won’t hold that against Times New Roman; it’s perfectly acceptable as fonts go. But it also means an alliance with historical conservatives, and that may explain the (possibly subconscious) love the Trumpers show for it.

That, and their venomous hatred of making any accommodation at all to those with any disability at all. Heaven forbid people should read what the US State Department writes.

A Modest Proposal

In keeping with Jonathan Swift’s 1729 satirical essay “A Modest Proposal”, I have a modest proposal of my own for the Trumpers.

It turns out, in Unicode, you can add diacritical marks (basically accents and such) to just about any letter you like. In fact, they compose in an unlimited way: you can add them on top of each other, to your heart’s content.

If you really don’t care about readability by those with visual impairments, and want to flaunt it by making things hard to read even by those with perfect vision, then the staff of the LingoJam web site has something for you: Cursed Text. ^[3]

Basically you give the Cursed Text generator some ordinary text, and it will add controlled amounts of chaos by putting in an absurd amount of diacritical marks. Here, for example, is how “US Department of State” would appear with a very modest amount of such chaos — maybe 5% of the amount possible in the UI on LingoJam. (Though I note that, ironically enough, it chooses by default a sans-serif typeface underneath all the cursing.)

That’s about as contemptuous of your readers as you can get, short of actually spitting in their eyes. Seems about on-brand for Trump.

I’m sure if the US State Department wants to use this as their new logo, a royalty agreement can be worked out for them to pay a very reasonable annual license fee to Your Humble Weekend Editor and the owners of the LingoJam web site.

The Weekend Conclusion

Look, they’re already determined to bring curses on themselves. Why not be straightforward about being a curse upon humanity? After all, they’re not shy about all their other evil behavior.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: Reuters Staff, “Typeface of ‘wasteful’ diversity: Trump’s state department orders return to Times New Roman”, The Guardian, 2025-Dec-09. ↩

2: Weekend Editor, “LM AIs Are Still Buckets of Warm Sewage & Broken Glass: An Agony in 7 Fits”, Some Weekend Reading blog, 2025-May-21.

The part about right-wing bias because of typefaces in newspapers for rich people is in Fit #4. ↩

3: LingoJam Staff, “Cursed Text”, web site accessed 2025-Dec-29. ↩

The Analemma

Incorrigible veteran readers of this Crummy Little Blog That Nobody Reads (CLBTNR) will perhaps remember a number of previous posts around this time of year, noting the analemma and that the day of earliest sunset is not the same as the shortest day of the year. ^{[1] [2]}

That’s all due to a wonderful former colleague who wrote an annual letter ^[3] many of us. For people who have no use for the idea of getting up at dawn, the time of sunset is the most important matter determining useful daylight!

If you were to photograph the position of the sun in the sky at the same solar time each day, say at local solar noon, you’d see a picture like the one shown here. ^[4] There’s considerable math to be done here ^{[5] [6]}, about the earth’s orbital dynamics. The spin axis is tilted (causing seasons) and the orbit is slightly elliptical leading to… well, peculiarities like the analemma.

In times past, I’ve done a custom calculation for the current year. But… honestly, the earthy’s orbit doesn’t change that much. The date of earliest sunset at my latitude might move 1 day, but it’s always December 7 or so.

Here’s the plot from a calculation I did in 2020 for the Boston/Cambridge latitude, showing the date on the horizontal axis and the time of day for various solar events on the vertical axis. The time of sunrise is the red curve on the bottom, local solar noon is the green curve in the middle, and sunset is the blue curve at the top.

As you can see:

• the earliest sunset was December 7,
• the good ol’ solstice will be in its customary seat at December 21, and
• the latest sunrise – for those of you leading a tortuously early-rising lifestyle – will be on about January 3rd.

For those of you who live at other latitudes, of course the result will be different. Rather than repeat my eccentric calculation above, you can simply read McClure at EarthSky’s account ^[7] summary of some results calculated by climate scientist Brian Brettschneider.

• Here on the map of North America you see the dates of earliest sunset and latest sunrise (along with the number of days in between), for various latitudes. It’s a function of latitude, so Europeans and Japanese can simply look at their latitudes on this map to get local results for their homes.
• If you’d like to get a full picture, including the southern hemisphere, have a look at the plot. It shows the earliest sunset and latest sunrise dates as a function of latitude all over the planet.
  • Of course no such thing happens at the poles, so the latitudes don’t go above 66°.
  • And of course everything reverses in the southern hemisphere.
  • And, the equator is a funky place indeed! The window between earliest sunset and latest sunrise is widest there, but… the difference in times is minimal there! So you’re seeing the smallest effect sustained for the longest time at the equator.

Now, personally, I’m a fan of cold and dark and snow. Winter is The Good Stuff. But I admit this is a minority taste. If you, like the Weekend Editrix, long for the return of the light… your sunsets are already moving in your favor, toward more light.

(Now, if only we can get “more light” in the US’s political situation, that would be good. And no, I do not mean “mehr licht” in the sense of Goethe’s last words!!)

So: the denizens of Château Weekend wish you more light, both physical and metaphorical.

Reminding Ourselves of Better Things

As another holiday custom, we like to attend some of the many, many musical celebrations of the holidays offered in the Boston area.

This year, as in recent years, that included the 116th annual Christmas Carol Serivce at Harvard’s Memorial Church.

Now, this is a very beautiful space, both for religious use and for concert use, and that night we had both. Sometimes it’s important to let the space operate on you, to see what emotions it will bring up, and what insights bubble up out of your subconscious.

Some things that struck me:

• The decorations worked subtly and well.
  • The flowers and ribbons in red contrast nicely with the dark wood, without glaring.
  • The candles (not especially visible in this photo) add a nice flicker effect that to me somehow lets me drift out of the mundane world. (I probably loved it even more as a kid; my adult self is uncomfortably aware of fire hazards in crowded old buildings.)
  • I also liked the rood screen at the front. It’s usually found in Catholic, Anglican, and Episcopalian contexts, so it’s a but unusual in what is billed as a “non-denominational Protestant” space. Still, it subtly suggests to me that “there’s something more here, beyond the usual space you’re in just now.”
• In the balcony/choir loft above and behind us, there is an impressive pipe organ! Combined with the effect of having the choir above and behind you, this has a strong effect of making the sound 3-dimensional, situating you in space rather than in just a room.

• The supporting columns are kind of interesting, when you look closely at the sculptures on their capitals. I’m always fascinated by that sort of detail: somebody went to a lot of effort to design and create those elaborate carvings; what might they have been trying to communicate?

  Some of it, at least, is clear.

  This is a memorial church, dedicated to the memory of those who died in the world wars. The names (at least of those Harvard associated) are carved on the walls, which always makes me feel a little creepy.

  Look closely at the photos of consecutive columns: they center alternating sculptures of a dove descending and an open-winged eagle. The dove descending is pretty straightforward: a reference to the holy spirit descending at the time of Jesus baptism, almost universally in Christianity parsed as a symbol of a divine blessing of peace. The eagle is pretty clear too, as a symbol of war – just look at some of the royal European escutcheons for some examples. So the columns say “alternating war and peace”, in a place of peace dedicated to the memory of war dead. That’s just about perfect.

  (When I mentioned this to the Weekend Editrix, she looked at me strangely and said, “You said that last year.” So much for my memory.)

  (Ok, there’s also a ram, a bull, and a lion at the corners of the capitals. As to the message there, I got nothin’.)

If for some reason you had the misfortune not to find yourself in Boston on the necessary date, you can watch the service on YouTube as shown here, and look through the program yourself. It’s worth your time.

The prelude music by and large didn’t move me much, but the introit (@35:42 in the video) was deeply moving and so other-worldly it brought goose-bumps. No, not from cold. The sentiment of Populus qui ambulabat in tenebris (“people who were walking in shadow”) has a lot of impact on me. Not the least because the US is currently walking in some very deep shadows.

The processional (@ 38:47 in the video) had a similar impact on me. Singing in Latin (“Adeste fideles”) of course is a strong childhood memory and here it was done in a building in which, for ages, people were expected to know at least some Latin. Its effect was multiplied by being in a group, in winter, in a building designed to work on my subconscious, with flickering candlelight… It was hard to keep emotional control then, and I’m tearing up a bit now just writing about the memory.

At this point, I believe I am legally required to approve, under the General Laws of the Commonwealth of Massachusetts. And I do so approve. Firmly.

The next piece, Palestrina’s “Alma Redemptoris Mater” (kind mother of the redeemer), also really got to me. The general 3D effect of having the choir above and behind us, the echos of the acoustic space, and the candlelit Latin polyphony really pushed my buttons. The words were attributed to Hermann of Richenau (1013-1054), so I felt connected to millennia of similar sentiments by those who came before me.

“Solstice”, by Carson Cooman, also struck me though in a different way (@ 1:03:00 in the video). It was composed specially for this performance. I liked the metaphor of darkness at solstice as like a high tide, with darkness lapping at our shores. It reminds me of many of the Davidic psalms, starting with a consciousness of darkness and falling short, then turning sharply (with a marked change in the tone of the organ music) toward the possibility of redemption:

We are going down now into darkness
And the plume-dark night, longest of all,
Looms just ahead. Each day long shadowy waves
Wash deeper on shores of light
But the high-water mark still stands
As we await high darkness,
Deep night spread out on our sands
Until no light is left;

And then at the bend of the year
Slow ebbing springs day free
As we, washed bright from night by night,
Leap shouting, bare, exultant
Over glittering sands of light.

(So, you see, I can react to singing not in Latin! Ok, it wasn’t my favorite music, but the meaning behind it packed quite a punch for those who could perceive it.)

“While Shepherds Watched”, by Alice Parker (@ 1:08:30 in the video) improvising on an 18th century theme by Supply Belcher, also was quite good. It was composed for the 100th annual service, back in 2009. Ok, it didn’t move me emotionally quite as much, but I did like the lively, almost round-like structure of the singing.

“Personent Hodie”, from the Piæ Cantiones of 1582 is one of my favorite songs of the season. Alas, they chose a Holst/Rutter adaptation which is… not my favorite. Check out the version from Loreena McKennitt, or the one from the Medieval Bæbes.

There was a congregational singing of “Hark! The Herald Angels Sing”, which always makes me giggle, because I am too much of a nerd:

• A herald is a messenger of a royal court, sent to give a message from a king.
• “Angel” comes from Greek ἄγγελος (angelos), or “messenger” as they carry messages from heaven.
• “Hark!” means “hey, listen – I’ve got a message for you”.
  So the title is “Listen up to my message of the messenger messengers singing.”

(You’re just gonna have to trust me that that’s funny… to minds sufficiently twisted a-widdershins.)

So what was the general theme?

The theme of all of the pieces that spoke to me, in retrospect, were about acknowledging our faults and sins, hoping to do better and be forgiven. Always a good sentiment; I was somewhat oddly thinking of the parallels to Jewish tikkun olam at the same time. Apparently my subconscious is inhabited by some crazy old syncretists.

There’s an emotion we inexplicably don’t talk about much: elevation. It’s how we feel when we imagine, witness, or participate in acts of great moral goodness. It makes me feel not just appreciation, but a profound, often tearful appreciation for how the world could be better, how I personally could be better, and that the work of making it so should be a happy working.

More of that, please.

A lot more.

For all of us.

The Weekend Conclusion

The Weekend Publisher and the Assistant Weekend Publisher wish me to remind you that cats have holiday traditions, as well. Here you see them attempting to confer, consult, and otherwise hobnob at the dinner table. (They are allowed on the table as long as they behave like gentlemen and remain at the Cat End of the table.)

They particularly like this season, but not because they are religious in any way that I can discern. Rather, it is Box Season. Large numbers of boxes begin arriving at the house. Their human servitors remove the annoying contents but leave the boxes, so that all is as it should be in Cat World.

You may not, personally, find boxes to be particularly fascinating. ^[8] Nevertheless, our holiday wish for you, from Château Weekend, is for your life to have more of a stream of things as delightful to you as boxes are to The Cats of Chez Weekend.

The times are dark. Let us try to bring in more light for each other.

And for any deities watching, who might feel inclined to indulge a fervent wish: Ceterum censeo, Trump incarcerandam esse.

Also, as recently seen: Index Epstein divulgandus est. (The Epstein files must be released – a worthy addition to the sentiment above, in its Cato-esque phrasing.)

Notes & References

1: Weekend Editor, “Winter solstice, Dodds’s Day, and the Weekend Editrix’s Day”, Some Weekend Reading blog, 2020-Dec-21. ↩

2: Weekend Editor, “Tis the Season… of the Analemma”, Some Weekend Reading blog, 2021-Dec-15. ↩

3: DW Dodds, “Analemma, my Anlemma”, Some Weekend Reading blog, 2020-Dec-21.

This was once a much-anticipated annual email from Doug to all his colleagues. ↩

4: D di Cicco, “Exposing the Analemma”, Sky and Telescope, June 1979, pp. 536-540. ↩

5: CH Holbrow, “Build Your Own Analemma”, arχiv 1302.0765, 2013-Feb-05. ↩

6: P Lynch, “The Equation of Time and the Analemma”, Irish Math Soc. Bull. vol 68, Summer 2012, pp. 47-56. ↩

7: B McClure, et al., “Your earliest sunset comes before the winter solstice”, EarthSky, 2025-Dec-07.

Images quoted here from EarthSky were taken, with permission, from the blog of Alaskan climatologist Brian Brettschneider:

B Brettschneider, “Daylight-Twilight-Astronomical Maps”, Brian B.’s Climate Blog, 2016-Jun-16. ↩

8: Unless you are a cat. If you are a cat who can read this blog, I would really like to hear from you. Please use the email or social media links at the top of each page. ↩

The Bad Old Days

Monopolies come in 2 kinds, broadly speaking: horizontal and vertical. (We’re glossing over mountains of detail, but this is as good a place as any to start.)

The Wikipedia explainers on vertical monopolies and horizontal monopolies are pretty good; the diagram at the right comes from those articles. It depicts, as an example, the phases of automobile manufacturing, distribution, and usage vertically. Horizontally are different companies that engage in each of those phases.

A vertical monopoly is a company that attempts to control a column, while a horizontal monopoly attempts to control a row:

• A vertical monopoly is where 1 company tries to be a controlling force in each of the rows, i.e., building itself along the entire column in the figure.

  It manufactures, distributes, sells, services, and garages cars in this example. This gives them opportunity for lock-ins: their cars take only their gas, their garages accept only their cars, their mechanics work only on their cars, their manufacturing workers and engineers are encumbered by non-disclosures to work only on their products, etc.

  Carnegie Steel would be an example from the 19th century: they owned iron mines, they owned coal mines, they owned coke ovens, they owned railroads, they owned steel plants, and so on. This led to a furious level of integration that let them control costs, but at the expense of extracting monopoly profits from the markets and driving out competition.

  Standard Oil was another such example in the 19th century: petroleum extraction, transport, refinement, and wholesale distribution were all under their control.

• A horizontal monopoly is when a corporation builds itself along a row in the figure, e.g., basically controlling all the production in one step of the manufacture of cars.

  If you control all the railroads, then you can make the steel companies pay you exorbitant fees to transport their coal, iron ore, and steel.

  There are numerous such examples in the US now, such as airlines, pharmaceuticals, meat packing, telecommunications, entertainment, and so on. Each of those is controlled by a very small number of companies, with cross-agreements among the competitors.

This caused all sorts of havoc in the late 19th century and the early 20th: periodic economic panics and depressions, mind-boggling inequality, political corruption in the service of the wealthy, and so on. It was fixed (mostly) over a period of decades, with anti-monopoly laws like the Sherman Antitrust Act of 1890, progressive taxation in the 1930s, banking regulation, and so on. This lead to what economists Claudia Goldin & Robert Margo called the mid-20th century “Great Compression” in a 1992 paper (riffing off the term “Great Depression”). ^[1]
Inequality shrank dramatically, banking was stabilized with FDIC guarantees and the Glass-Steagall acts of 1933 to control their risk taking, the Federal Reserve could moderate economic downturns, and so on. This led to a period of stable growth.

The Bad Nowadays

Then we repealed all that, or let conservative Supreme Courts pick away at it until it was neutered, or at least declined to enforce it. (Similarly to the way we’ve allowed civil rights and voting rights to wither.)

And now we’re back to the Gilded Age: by the Gini coefficient, which measures inequality, we’re in a second Gilded Age. We should expect monopolies, panics, economic collapses, and political corruption. So… here we are:

• According Williamson & Lindert, writing for the Centre for Economic Policy Research (CEPR) ^[2], American growth and inequality since 1700 show we are now at the inequality peaks of the first Gilded Age.

  Here we reproduce their Figure 2, which has the goods. Note that the US was always a pretty unequal place, with an extraordinary interlude from 1940-1980. The post-WWII tax reforms and opened access to education (though sadly excluding most minorities and women), produced the “Great Compression” we cited via Goldin & Margo above.

  Here it’s clear: beginning around Reagan, we began re-imposing the mechanisms of inequality with huge tax cuts for the wealthy, benefit cuts for the poor, and massive corporate welfare.

  We are now, by the numbers, in a Second Gilded Age.

• As former Labor Secretary Robert Reich, Obama economic advisor, Harvard/Brandeis/Berkeley professor has recently reminded us ^[3]: now the pay gap between workers and CEOs is 351-to-1 vs 21-to-1 in 1965.

  One reason wages can’t go up is because all the increased profits from increased productivity have gone to the top.

  (Reich proposes an additional corporate tax based on the CEO to (median?) worker ratio. While sensible, that, of course, will have to wait for the return of a degree of sanity to US politics.)

• Not enough for you? How about the Roman Empire?

  Scheidel & Friesen, writing in the Journal of Roman Studies in 2009 ^[4], go through all the elaborate details to estimate the Gini coefficient for various phases of the Roman empire. Their conclusion (bottom of p. 86): 0.42 - 0.44.

  Note this very carefully: with the US at a Gini coefficient of around 0.5, we are now more unequal than the Roman empire, with its über-wealthy aristocrats vs its slaves.

We’ve also declined to enforce anti-monopoly laws in any meaningful sense. (And now, it appears that having a Trump associate involved, or paying a bribe to Trump, is a pre-requisite for getting mergers approved.)

Here are some examples of how badly concentrated industries in the US have become in the last 40 or so years since Reagan. They show the tree of corporate mergers leading to just a few behemoths left today. (Click to embiggen any of these pictures.)

• Defense contractors (upper left) have collapsed from 75 companies to just 5.
• Airlines (upper right) have collapsed from 34 carriers to 5.
• Pharmaceuticals have done something similar. Here we show the corporate ancestries of Pfizer (combining 52 companies into 1 giant), and Sanofi (combining 18 companies into 1 giant).
  (Note that Sanofi is largely European; corporate mergers to form oligopolies is a phenomenon common in most of the developed world. Hence, so also is revenant fascism.)
• Finally, at the bottom, we show how American banking became so concentrated: 37 banks became just 4 “too big to fail” banks that have their tendrils into everything. This is also why I’ve had 5 separate banks since coming to MIT as a grad student, despite never changing my account: the banks just kept eating each other!

These are huge concentrations of corporate power. With the ability of corporations to donate to political campaigns, particularly soft money and dark money, they are concentrations of political power as well.

It’s not just corporations that seek to monopolize things.

An example that stuck in my youthful memory was from 1980, when the Hunt brothers attempted to corner the world silver markets, leading to Silver Thursday on 1980-Mar-27 ^[5]. With the Iran hostage crisis in full flare, the prices of gold and silver climbed as investors worried about war. The billionaire Hunt brothers sought to control substantially all the silver on the world markets, with a series of leveraged commodity moves.

At one point in 1979, they apparently controlled over 100 million troy ounces of silver, about 1/3 of the world’s silver not held by governments.

This caused a collapse and commodity market panics, which had to be bailed out by a consortium of banks. (NB: They provided a bailout to the Hunt brothers, not to people who were damaged by their monopoly.) If that had not happened, a number of brokerages and banks might have collapsed, having lent money to the Hunt brothers for their boondoggle.

This is what happens when we allow too much concentration of wealth and power, with little meaningful restraint: they will attempt to achieve complete control, and will require massive bailouts when they fail.

This is what “privatize the profits, socialize the losses” means. It should have been obvious in 1980, but here we are, 46 years later, still avoiding the lesson.

… And Now, Today’s Outrage du Jour

So it should come as no surprise that our modern oligarchs pursue the same strategy.

While I’m familiar with “Moore’s Law is dead” as a (mildly questionable) saying, I haven’t read the blog of that name. But they’ve reported an important story on their blog and their YouTube channel that I haven’t seen much in the traditional media. ^[6]

Just as the Hunt brothers spiked the price of silver, the writers noticed a 156% jump in DRAM over a period of about 3 weeks. It’s enough that the DRAM alone would cost more than the whole computer did before the price jump. DRAM is, indeed, becoming almost unobtainable. Apparently several DRAM manufacturers have contacted wholesalers and retailers, to see if they could buy back inventory.

Their analysis:

So what happened? Well, it all comes down to three perfectly synergistic events:

1. OpenAI executed two unprecedented RAM deals that took everyone by surprise.
2. The secrecy and size of the deals triggered full-scale panic buying from everyone else.
3. The market had almost zero safety stock left due to tariffs, worry about decreasing RAM prices over the summer, and stalled equipment transfers.

Apparently OpenAI signed deals with Samsung and SK Hynix – with near simultaneity – to acquire 40% of the world’s DRAM supply for themselves alone. They even managed to keep Samsung and SK Hynix from knowing about each other’s deals, to prevent them from going up in price.

Add to that the tariff chaos, and you have a situation where the DRAM manufacturers had no slack inventory at all.

And the weirdest part: they’re buying uncut, unfinished wafers. They’ll apparently be stockpiled, either to be finished into usable modules later, or just to cut supplies to competitors else now. Manufacturers are now quoting 13 month lead times on memory.

That makes it look like OpenAI isn’t just defending their own supply of memory, but attempting to choke the market to cut off anybody else. There are reports that OpenAI is attempting to buy up the DRAM manufacturing equipment as well, to deny future manufacturing capability.

This is a classic monopolist’s move!

The Weekend Conclusion

Look, billionaires are just no good. We should tax them down to, say, $100 million each, maybe?

We remind everyone of screenwriter John Rogers’s 3rd Rule of Crime:

Rule 3: Nothing ever stops until a Rich White Guy goes to jail.

That’s the moderate solution. The other solutions probably involve tumbrels.

(Ceterum censeo, Trump incarcerandam esse.)

Addendum 2025-Dec-15: Historian Heather Cox Richardson Explains it All

I try to listen to American historian Heather Cox Richardson on an regular basis. Her Letters from an American is worth checking frequently. I also like her YouTube videos, if only to hear her calm voice, explaining the horribly fascist reality of American politics at the moment.

This video is an excellent example, showing how relatively lower income inequality in the mid-20th century was a departure from the norm: the oligarchs think it is normal that they should rule. She relates the variety of ways the “reactionary right” has tried to reassert economic and political power, to undo the 20th century reforms and re-institute their will as law. It’s all there: the racism, the xenophobia/deportation fever, the moral panic over LGBTQ folk, the regressive tax cuts piling wealth into the top 1%, and so on.

Very worth 15 minutes of your time!

Notes & References

1: C Goldin & R Margo, “The Great Compression: The Wage Structure in the United States at Mid-century”, Qrtly Jnl Econ 107:1, 1992-Feb-01, pp. 1-34. DOI: 10.2307/2118322.

NB: To avoid a regrettable paywall, the link above is to a working paper version, NBER Working Paper #3817. ↩

2: JG Williamson & P Lindert, “Unequal gains: American growth and inequality since 1700”, Centre for Economic Policy Research VoxEU column, 2016-Jun-16. ↩

3: R Reich, “How Can Outrageous CEO Pay be Stopped?”, Robert Reich Substack, 2025-Dec-09. ↩

4: W Scheidel & SJ Friesen, “The Size of the Economy and the Distribution of Income in the Roman Empire”, Jnl Roman Studies 99, 2009-Nov. DOI: 10.3815/007543509789745223. ↩

5: Wikipedia Editors, “Silver Thursday”,Wikipedia, downloaded 2025-Dec-05. ↩

6: “Tom”, “Sam Altman’s Dirty DRAM Deal, Or: How the AI Bubble, Panic, and Unpreparedness Stole Christmas”, Moore’s Law is Dead blog, 2025-Nov-24. ↩

The Woefully Misinformed are Now Protesting… Batteries?!

We’re used to a sort of know-nothing NIMBYism now. People oppose vaccines because they’ve been duped, they oppose housing even in places where housing is desperately needed, and so on.

Recently I learned a new sort of know-nothing NIMBYism: opposition to battery storage of electrical power at the grid level, to level out power demand. ^[1]

Without such batteries, we need lots more “peaking” generators, to supply electricity less efficiently but on demand at high usage times. The rest is very efficient baseload generators. But with batteries, the efficient baseload generators can store their excess and release it during peak demand. The round-trip efficiency of baseload generators plus the batteries exceeds that of peakers.

Also, battery storage facilities are very important for large-scale, green solar and wind power generation. They are intermittent, but coupled with batteries they become quite acceptable for baseload purposes.

However… the very wealthy fossil fuel incumbents will do just about anything to encumber green energy, as we’ve previously documented on this Crummy Little Blog That Nobody Reads. ^[2]

And so it is here:

• Even though this will make the grid more reliable, admit more green energy generation, and bring down electricity costs by displacing the expensive peakers, people have been bamboozled into thinking it will raise their electric bills&helllip; because “green” means “bad” to right-wingers.

• Someone has convinced the residents of Oakham, Massachusetts that batteries are always catching fire.

  The distinction between “lithium ion” vs “lithium iron phosphate (LiFePO4)” battery chemistry just doesn’t penetrate their heads. They see “lithium” and think “fire”. (This is why they took the scary word “nuclear” out of “nuclear magnetic resonance imaging” (NMR) and now call them “magnetic resonance imaging” (MRI) scans, to appease the hysterics/testerics (just heard that word!) who get jumpy at the word “nuclear”. There is of course no radiation at all; it’s just the magnetic moment of the nuclei that’s being flipped around and measured.)

  • There was a fire at a facility in Monterey, California. It used batteries with a different chemistry, indoors instead of outdoors, without individual containment housings, without the computer control of thermal characteristics, and before any of this was regulated. In other words, nothing much to do with the present.
    
  • Indeed, according to the EPRI’s BESS (“Electric Power Research Institute” and “Battery Energy Storage System”) database, fire failure mode has gone down 98%, as shown here. ^[3]
  • Somehow nobody ever asks about the fire risks of natural gas pipelines, and even the distribution system into individual houses!
• The plant is proposed on the site of a former auto junkyard, as shown in the aerial photo and rendering shown above. So it’s not like they’re taking over precious green space.
• The signs think that – somehow – the battery storage facility will pollute their drinking water. I have absolutely no idea how that idea came about.
• Even more bizarrely, they think the batteries will somehow be loud, and annoy the people in nearby houses. “Nearby” here is at least 1/4 mile away, so that makes essentially no sense whatsoever.

Quoting Brian Benito, representing the builder Rhynland Energy:

“What I also heard was a lot of misinformation, unfortunately,” he said. “And that information, once it takes hold, is very hard to dislodge.”

As activist Joe Curtatone put it:

“Misinformation about energy storage is spreading faster than facts,” he said. “This isn’t just a debate over technology, it’s a battle over truth.”

Indeed! It’s almost as though there’s organized resistance to green energy, flooding the zone with propaganda in favor of the fossil incumbents, isn’t it?

A New Internationalization/Keyboard Shortcut on Macs

Ok, enough serious stuff!

But on a related note, one of the things right-wingers eye with suspicion is any internationalization whatsoever of the US. Let’s see what’s happening in software that might get their goat, if only they knew about it. (Metaphorical goats. Actual goats, q.v.)

It turns out that in German there’s a funny character: ß, known as the “eszett” or “sharp s”. It means the “s” sound as in the English word “hiss”, completely sibilant and unlike what English writers would render as “sh” or “zh”. It looks like a Greek β, but is quite distinct.

When rendering in character sets that are less than completely accommodating, one writes “ss” as a reminder that it’s an “s” as in “hiss”. For example, the German word for “foot” is “fuß”, which would be written “fuss”.

Now the place where that interacts with computers is on MacOS, which takes seriously the duty to work for almost all languages.

There’s a program called “ssh”, for “secure shell”. It doesn’t matter for our purposes exactly what it does, just take my word for it that it’s a thing some of us use daily. Someone thought, as reported by “benjojo” below, that maybe something interesting would happen if you typed “ßh” at the command line:

The first bit of text shows that, if you type just “ssh”, you get the help text for how to run ssh. The second bit of text shows that, if you type “ßh”, MacOS translates “ß” to “ss” and you get the same thing! (NT folk who are non-members of the neurodivergent computer-oriented tribe of icky nerds will just have to take my word for it that this is amazing and hilarious.)

So I couldn’t just take his word for it, I had to try it. Here is the evidence on my MacOS system (Monterey 26.1, vintage 2025-December). Indeed, the text at the top and bottom are the same: “ßh” gets ‘translated’ into “ssh”.

Someone at Apple had better be giggling right now, and giggling pretty dang hard! Because, intentional or not, this is just brilliant.

It makes me wonder – but not enough to try – what it would do with the ð and þ (eth and thorn) characters? Those used to be in the English alphabet, representing the “th” sound, voiced and unvoiced, respectively. ^[4] Any suggestions for Unixoid commands involving “th”?

Windows 11 Finally Makes Sense!

All the big CEOs are convinced LLM AI is going to make it possible for them to fire there employees and rake in the cash. No less than Microsoft apparently is all-in on that idea, which makes sense given their “investments” in data centers.

From Steve Lieber on Mastodon comes an interesting juxtaposition of 2 facts from TechCrunch and Reddit:

Ok, when you put it that way, Windows 11 makes sense: it didn’t even have a chance of working?! Suddenly, I understand why Windows is so difficult & unreliable that only an MBA could love it.

Really the only surprise is that they admit it?

Yuletide… Celebrations?

We have now entered the season of the year when all sorts of year-end celebrations happen in a variety of traditions. Most of them are beautiful, some are very silly, and a select few are both beautiful and very silly.

Of course you know which of those groups fascinate me most, don’t you?

Gävlebocken: The Gävle Goat

In the Swedish city of Gävle, they have a tradition dating back to about 1966.

For no reason that is particularly obvious to me, they decided to build a giant “yule goat” sculpture out of bales of hay, light it up, and have various parties, festivals, and so on. I don’t get the Gävlebocken (“Gävle goat”) part, but having a reason to celebrate warm feelings with each other at a cold & dark time of year makes perfect sense.

There is another bizarre “tradition”: the young men of the area attempt to set fire to the Gävlebocken. As of this year, 49 out of the 52 goats have been burned down. This is, of course, illegal in highly civilized Sweden. But… things happen.

Here you see a picture of the 2025 iteration of this straw goat tradition. ^[5] And yes, of course there’s a live webcam so you can check in on the state of the goat, to see if it’s on fire.

I don’t actually know which side to root for here. I suspect the local fire department and the elaborate system of goat guardians have a safety system all worked out, since it’s been needed 49/52 times.

I wish the goat good luck. To the extent that “luck” means anything at all, let alone for an inanimate sculpture out of hay. Perhaps the Scarecrow of Oz would like a word? He is, after all, the wisest being in Oz and has previous experience with being made of hay and escaping attack by fire. (Admittedly, a witch instead of pranksters, but still… experience.)

Krampusnacht!

And now, on to serious matters: our second annual ^[6] “Gruß vom Krampus!” post. (Remember that ß character above? “Gruss” means “Greetings”.)

December 05 is Krampusnacht, the night when St Nicolas and his “assistant” Krampus ^[7] come to evaluate children.

As we wrote last year upon this occasion:

One of the nicer folk-myths around European Christianity is a visit from the rather gentle St Nicholas, encouraging goodness in children. Of course this is thoroughly corrupted with greed for presents, but at least the seed was one of kindness.

A rather bizarre turn is that we just can’t seem to leave a good thing alone, but must always go full-on Manichean by introducing a dark counterpart. Like the Babylonian exile exposed Jews to Zoroastrianism which raised the profile of the Satan, we seem fascinated with good/evil counterparts instead of just concerning ourselves with good.

And so it is, even with the gentle St Nicholas and his cartoonish successor Santa Claus. In Alpine folklore, he is accompanied by (not “opposed by”; they always come together) a figure called Krampus. St Nicholas blesses the good children, and Krampus… well, he has business with the bad children:

• He’s always described as dark and hairy, with the horns of a goat and a long pointed tongue. (Sometimes ridiculously long, as in he can pick up children with his tongue.)
• He carries chains and manacles, either to represent the binding of the Devil or with which to bind bad children.
• One foot is a cloven hoof, while the other is mysteriously not.
• He carries birch rods with which to whip moderately bad children.
• He also has a basket or a bag, for children who are more spectacularly talented at being bad. He’s said to stuff them in the basket, kidnapping them either to be drowned, or eaten, or taken to Hell. (Or, in some versions to Spain. No idea why Hell and Spain should be so linked? I also wonder if the American phrase “going to hell in a handbasket” is related to Krampus and his basket?)

Thus the traditions of the more remote Alpine places, where conformity with suspicions by the distant medieval church could be regarded as rather more optional. Today, it’s supposed to be a fun thing to do with kids, complete with parades.

People dress up as Krampus and scare children, in what I’m sure the children think is a totally fun prank. Occasionally after attempting to birch a child, parents feel inspired to punch out a Krampus cosplayer, which I’m sure is also a totally fun trip to a local hospital.

Krampusnacht, or Krampus Night, is December 5th. St Nicholas and Krampus visit houses with children for gentle congratulations & blessings from St Nicholas… or rather more boisterous moral instruction from Krampus.

Once again, here at Château Weekend, we politely wonder if the esteemed Mr. Krampus could come pay a visit to evaluate Mr. Trump for deportation to Spain… or perhaps even warmer climes? I mean, he’s trying so hard to earn that privilege!

The Weekend Conclusion

Ok, the battery thing is just dispiriting; all the disinformation seems to pull to the right-wingers, here toward fossil fuels. But beyond the cruelty and stupidity of right-wing fascism revenant worldwide, our world is also absurd in amusing ways… sometimes. Let’s enjoy the silliness of the rest of the stories.

And enjoy each other, as we are all, in the end, quite silly.

So enjoy the surreal. At least if, like me, you love surrealism.

Which you should!

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: M Wasser, “As Mass. pushes for big batteries on the grid, some communities push back”, WBUR News, 2025-Nov-10. ↩

2: Weekend Editor, “The Republican War on… Weather?!”, Some Weekend Reading blog, 2025-Aug-25. ↩

3: Electric Power research Institute, “BESS Failure Incident Database”, EPRI web site, downloaded 2025-Dec-04. ↩

4: Remember when you were a kid, reading old books, and you kept coming across phrases like “ye olde shoppe”?

It was never meant to be pronounced with a modern “y”. It used to be written “ðe” and when typographers no longer had the “ð” character they temporarily replaced it with a “y”. Later we standardized on replacing both “ð” and “þ” with “th” and inferring the pronunciation from context.

So, yeah, it’s written “ye olde shoppe”, but pronounced “the old shop”. ↩

5: Visit Gävle Staff, “Gävle’s brilliant Christmas symbol”, Visit Gävle web site, downloaded 2025-Dec-04. ↩

6: Weekend Editor, “Gruß vom Krampus!”, Some Weekend Reading blog, 2024-Dec-06. ↩

7: Wikipedia Editors, “Krampus”, Wikipedia, downloaded 2025-Dec-04. ↩

The Season

I know you were expecting me to say “must be the season of the witch”, after the Donovan song from 1966/1967. While the mononymous Donovan and his song presaging the psychedelic pop era have their charms, Hallowe’en is regrettably passed. And frankly, New England has a shortage of witches this century. (Yes there are the Wiccans. They’re… well, peculiar… but in no way frightening.)

No, the autumn here in New England is the season of the leaf.

Often you’ll just be going along, and see a sudden flash of color when a tree shows its leaves in a shaft of sunlight. Here’s a random tree in a church parking lot, showing brilliant reds and oranges because an opening let through a column of sunlight to set it off.

I mean, it’s pretty, sure.

But what I really like is the serendipity. You’re just walking along, not thinking about what you see around you and… Nature grabs you by the frontal lobes & says, Look!

Other times, the beauty is just in an unexpected place. This is the Weekend Editrix’s shade garden, in a shady hillside behind Château Weekend. It’s quite nice in the summer, but I was struck by its beauty now as cold and dark are setting in. The hostas in particular are going dormant, to get ready for winter. As they do, their leaves turn a strikingly bright shade of yellow. It’s as though they’re waving good-bye, reminding me that they’ll be back in the spring.

(And if you’ve ever worked with hostas, you know they’ll be back with a vengeance.)

… And the Cleanup

But with all that beauty comes the cleanup, as is so often the case. That means leaf raking/blowing, bagging up, and disposing of the bags of harvested leaves. A lot of that. It’s back-breaking work for an old guy like me, or at least back-sore work.

Here you see this morning’s harvest ready for pickup by our town for composting. There are 40 bags here, each nominally 30 gallons. Though really, that 30 gallon figure assumes you fill only to the fill line which is maybe 3/4 of the way up. These are all full, so probably 40 gallons each.

Together with the 20 bags that were picked up 2 weeks ago, that brings the total to 60 bags of leaves, approximately 40 gallons each, or 2400 gallons. (That’s just a hair over 9 cubic meters.)

I wonder how many leaves that is? Anybody feel like doing a Fermi estimate for me? I tried it with estimating the number of maple spinners/seeds, and got a surprisingly high number.

Now, you may think 60 bags is a lot of leaves, and I agree with you. But the truth is that this is likely only about halfway through the season; last year we did about 120 bags total.

So, there’s some more time with a sore lower back ahead for me. Or, possibly, hiring somebody to help. But it’s overall enjoyable outdoor work so long as I do it in short spurts.

Addendum 2025-Nov: The Total

It ended up being a total of 114 bags of leaves this year. Ouch.

The Weekend Conclusion

The work of preparing for winter each autumn is something I’ve enjoyed since childhood: raking up the leaves, clearing out the gutters & downspouts, bringing in the garden hoses to prevent freezing, and so on.

As you can see here, the Weekend Publisher (the giant black cat) and the Assistant Weekend Publisher (the smaller tabby) are both engaged in winter preparations of their own. They are test piloting the winter comforter on our bed, captured here in an innocent-looking photo from about 3am. Normally they have a dominance battle for space; here we’re seeing the result after they’ve declared pax.

I see yesterday was a very good day for the Democrats. May there be many more, so we can eventually remove, indict, convict, and imprison as many Trumpistas as possible. Then we also can declare pax.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

Nope.

Hank Green: Boggled by Circular Investment Flows

While checking in with Hank Green, I came across a video he did on the circular investment pattern in AI companies. Now, it’s the usual Hank fare: fast talking, “gee, isn’t this interesting”, and lots of fun data to think about. If you like that kind of thing, he’s a master of the form, managing to be simultaneously informative and entertaining (as one would expect of a science popularizer!).

Digging Deeper

But let’s dig into the primary sources, as we often do on this Crummy Little Blog That Nobody Reads (CLBTNR). He’s talking about a recent Bloomberg article ^[1], which contains the graph shown here. (Definitely click to embiggen!)

Basically, there are 3 sorts of actors in this drama:

• The chipmakers like Nvidia, AMD, and (to some extent) Intel. They make the chips, mostly GPUs, that power the matrix calculations used in what amounts to neural net LLMs.
• The data center operators like Oracle build huge data centers with enormous computing power. They rent this out to the AI companies, q.v. (They also consume entire city’s worth of electricity and guzzle clean water for cooling; the rest of us would probably prefer not to get higher electricity bills and have more water available.)
• The AI companies who rent this compute capability. Sometimes these are upstarts like OpenAI (worth a mere \$500 billion, also with a mere \$12 billion revenue and negative earnings). Sometimes they’re Microsoft and Google, who are maddeningly determined to force AI into everything, whether you want it or not. (I do not.)

Sometimes the middleman, the data center operator, is there and sometimes it’s not because the data center has been absorbed into a giant like Google or Microsoft. But that’s more or less the dramatis personae.

Now, on to the drama. Here are a couple examples from the opening of the Bloomberg article:

• Nvidia ‘invests’ \$100 billion in OpenAI, to fund a data center with the electrical consumption of a major city. In return, OpenAI commits to buying billions worth of Nvidia chips.
• Advanced Micro Devices (AMD) and OpenAI have a similar deal, on the tens of billions in scale.
• OpenAI struck a \$300 billion deal with Oracle to build massive data centers, powered with Nvidia chips. Oracle is then renting that capacity back to OpenAI, with guarantees that OpenAI will lease all of it. Oracle can now book \$100’s of billions in revenue… sometime in the future from a company with \$12 billion in revenue and negative earnings… somehow.
• Similarly, Nvidia has ‘invested’ in CoreWeave, ‘sold’ them chips paid for out of that investment, and guaranteed to buy all the compute power that CoreWeave’s AI customers don’t buy. That’s a great risk arbitrage for CoreWeave, but it means Nvidia’s taking almost insane levels of risk.

In other words, the hardware makers are paying their customers to buy their products. This is not outside investment, it’s just a handful of companies moving money around and variously calling it ‘investment’ or ‘revenue’, as they please.

There are tons of other examples in the Bloomberg article. The graph above summarizes just some of it. A couple dozen companies are shifting around commitments to invest, then hardware, and finally services. Sometimes this is an investment, sometimes it’s revenue.

It looks corrupt as hell to me, and that’s not even counting Trump’s extortion of part of the cash flow to Nvidia and AMD. ^[2] It also looks like the cross-selling financial ouroboros, among late-90s startups, just before the dot-com crash.

In fact, this begins to resemble the 19th century corruption of the Gilded Age, which must now regrettably be called the “First” Gilded Age, the “Second” being now. Between the circular movement of money, bizarre accounting for when it gets called revenue, and Trump’s extortion of a cut of the trade, this is exactly what was done then ^[3]:

“This is a government of the people, by the people and for the people no longer,” former president Rutherford B. Hayes wrote in his diary in 1886. “It is a government by the corporations, of the corporations and for the corporations.” Politicians took spectacularly handsome bribes from corporations and demanded kickbacks as the helping hand they extended often came with an open palm.

We really are in a Second Gilded Age of corrupt oligarchs, monopolies, and politicians, aren’t we?

A Contrary Opinion

Now, not everybody agrees with me. (Sadly.)

But in a spirit of objectivity that is the sine qua non of all scientists, let’s have a look at another Bloomberg interview that offers a contrary opinion.

This one is with Mandeep Singh, their Bloomberg Intelligence Global Head of Technology Research. A heuristic I learned many years ago is perhaps too sarcastic, but sometimes applies: the importance of your position is inversely proportional to the number of words in your title. Example: “President” is pretty important. Example: “Deputy Undersecretary for Intergovernmental Affairs in International Cheese Trade” is… less important. I’m not saying that this applies to Mr. Singh, but I am revealing to you my bias. Discount appropriately.

His argument is, in essence, that AI demand will definitely undergo hyperscaling levels of growth, because everybody wants it. Now, that’s contrary to my experience, where pretty much nobody wants it, and examples abound of AI used ignorantly create everything from absurdities to life-endangering hazards. But, if his “definitely” scenario is true, in order to profit from it you need to grow as fast as possible.

The circular funding arrangements that appear so corrupt to me, are to him just a way of companies lending each other resources to grow.

Will it collapse? Singh is optimistic:

… yes, there will be probably some misallocation of capital that we’ll find out in retrospect that this capital was misallocated in some way. But right now, it’s very hard to question the pace of this build-out because there’s still that big gap between demand and supply. And until that narrows, it’s hard to question why capital is going in this domain, because, I mean, it should.

Now, I think he’s deeply deluded: the Dutch tulip prices in the 1630s kept going up too… until they didn’t. But that’s his viewpoint, presented in as honest a fashion as I am capable of doing.

There is, of course, uncertainty! In the words of the Bloomberg article, describing the power of Sam Altman, as CEO of OpenAI:

Altman “has the power to crash the global economy for a decade or take us all to the promised land,” Stacy Rasgon, an analyst with Bernstein Research, wrote in an investor note this week. “Right now we don’t know which is in the cards.”

Personally, I think he’s driving all of us into a crash, or worse.

The Weekend Conclusion

Go look at that Bloomberg diagram which so fascinated Hank. It’s pretty damning.

AI/LLMs are a bigger bubble than the 2007-2008 financial panic, and bigger than the 2000 dot-com crash. This time, with what looks like a side of self-serving kickbacks.

Didn’t that used to be illegal?

Here at Château Weekend, it’s oligarch crap like this that made us reallocate our retirement portfolio to be the most defensive it’s ever been in our lifetimes. We still don’t know if that will be enough.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: E Forgash & A Ghosh, “OpenAI, Nvidia Fuel $1 Trillion AI Market With Web of Circular Deals”, Bloomberg, 2025-Oct-07, updated 2025-Oct-08.

NB: Regrettably paywalled. An archive version is available here. (You might have to pause your VPN.) ↩

2: H Lowenkron, M Sasso, & I King, “Nvidia, AMD Reach Deal to Give US a Cut of China AI Chip Sales”, Bloomberg, 2025-Aug-10, updated 2025-Aug-11.

NB: Also regrettably paywalled. An archive version is available here. (You might have to pause your VPN.)↩

3: C Klein, “How the Gilded Age’s Top 1 Percent Thrived on Corruption”, History.com, 2020-Jan-27, updated 2025-Jun-30. ↩

On the Origin of Dr. Who

In the UK, there’s a science fiction TV series called Doctor Who. It takes the concept of ‘science’ very loosely, indeed as it also takes set design, plotting, plausibility, and more or less everything else. It does, however, have its aficionados who love it to some degree because of its cheesiness.

This commentary about Doctor Who showed up on BlueSky. It is alleged to be a screen capture originating with @stevewriteswords.bsky.social, though I have been unable to verify that. So keep in mind that it might be fake; but given the mind-numbing wooden-headedness of AI LLMs, I think it’s probably real.

It says (emphasis added):

The first known TV series with episodes is the original Doctor Who, which began airing in 1608 on the BBC. This series, created by William Shakespeare, was a hit due to limited entertainment options at the time.

A TV series on the BBC… in 1608… created by William Shakespeare.

And people want to trust their code, their security, their finances, their medical care, their taxes, and everything else to machines stupid enough to say this?

More like, as one wag recently said, AI LLMs are like pouring asbestos into the walls of our intellectual infrastructure, for which we will spend generations digging back out and disposing of it safely!

Remember how bad an idea asbestos turned out to be?

The Weekend Conclusion

Intellectual asbestos, I say. Asbestos!

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

Nope.

Some Advice From A Little Girl

There are a variety of videos of this sort on YouTube. This particular one is from an account called “FurFamily”, which seems to consist mostly of cute animal videos. (However, I note that I couldn’t find this video directly linked in their pages, so it may be in the process of being suppressed? Hence it’s archived here, for posterity.)

She’s making a very useful point about the physics of zip ties: they mightily resist tension, but are relatively lame about friction across the tie.

Therefore, using her shoelaces, she can apply enough friction to heat the plastic and rip through it quite quickly.

But don’t forget: At the end of this physics experiment, she says “And then you’re free.” But… her shoelaces are at that point tied together – a configuration only good for sitting or lying down, not for walking. Or running. So, if you try to replicate this physics experiment and are for some reason in a hurry, remember shoes must first be retied in a more conventional manner! (And while she uses a square knot, perhaps a bowtie would be easier to undo at the end.)

I guess if you insist on wearing loafers in fascist-infested areas, you should probably have a “decorative” loop of string around your wrist?

The Weekend Conclusion

Sound advice, in case of kidnapping by fascists (or even garden-variety kidnappers).

I’m way too old to be put in a position to do this personally, but it seems like a regrettably useful thing to know.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

Nope.

Doctorow on the Inevitable

Cory Doctorow is a modern Canadian/British fiction writer and tech journalist of some note.

In fact, he is of such note that not only is there a Wikipedia page on him (link above), he is the subject of a joke in Randall Munroe’s XKCD #239. He was said to blog from a high-altitude balloon, while wearing a red cape and goggles. Showing off his famous ability to take a joke, he then showed up a few years later at a conference appearance with Munroe, wearing a red cape and goggles, to Munroe’s evident delight.

You know you’re part of the modern internet intellectual elite when XKCD makes fun of you, and you get to make fun back.

Doctorow’s opinions on the current LLM version of AI aligns more or less with ours, here at Château Weekend: BS firehoses and bowls of warm sewage & broken glass, best approached not at all, or at least with appropriate safety equipment.

While I’m not one of his regular readers, his latest summary of the causes of the AI bubble and its imminent collapse ^[1] caught my eye.

First, he has an interesting insight as to why all the LLM AI development seems to be coming from the likes of Google, Microsoft, and “startup” that soak in billions of investment (emphasis added):

… the AI bubble is driven by monopolists who’ve conquered their markets and have no more growth potential, who are desperate to convince investors that they can continue to grow by moving into some other sector, e.g. “pivot to video,” crypto, blockchain, NFTs, AI, and now “super-intelligence.” Further: the topline growth that AI companies are selling comes from replacing most workers with AI, and re-tasking the surviving workers as AI babysitters (“humans in the loop”), which won’t work.

We’ve allowed so much concentration of capital in oligarchs and in about 7 giant tech companies that their growth alone determines our economic future. They are desperate to “pivot to” something that will grow. (Whenever I heard management say “pivot to X”, for whatever value of X, I was always disappointed that they never admitted they were wrong about what they demanded we do instead of X in the past.) In this case, the “pivot to AI” has management drooling so hard because they fantasize they can jut fire most of those pesky employees, with their annoying demands for pay, insurance, time off, and retirement. (Not to mention diversity, equity, and inclusion.)

This is exactly the argument made in the Industrial Revolution for laying off cloth-makers and letting them starve. Brian Merchant’s excellent history, Blood in the Machine ^[2], illustrates this in great detail with comparisons to modern oligarchs and monopolies.

Merchant quotes the historian Frank Peel, capturing the mood of the elite of 1811 (and of today!) in their contempt for workers thusly (p. 44), with the suggestion of the ‘rational’ economic alternative for workers:

“Had they been better instructed, they would have known that it was their duty to lie down in the nearest ditch and die.”

In 1811 at the height of the cloth-making revolution in England, oligarch, aristocrats, and monopolies were the rule of the day. This is the inevitable way in which those things warp human minds. Like the fictional ring of Sauron, this sort of economic power tempts with great fantasies of fascist power, but in the end morally rots the holder to destruction.

That is, of course, a dark and hopeless fantasy on the part of the wealthy:

Finally: AI cannot do your job, but an AI salesman can 100% convince your boss to fire you and replace you with an AI that can’t do your job, and when the bubble bursts, the money-hemorrhaging “foundation models” will be shut off and we’ll lose the AI that can’t do your job, and you will be long gone, retrained or retired or “discouraged” and out of the labor market, and no one will do your job. AI is the asbestos we are shoveling into the walls of our society and our descendants will be digging it out for generations …

The comparison to asbestos is apt: we are polluting much of our information resources with AI slop that is either trivial or outright false, and making it harder and harder to tell what is AI slop and what is not. Having had to have asbestos removed from an older house, this hits home for me as a near-exact truth.

The financial arrangements are equally inane, in a way that utterly boggles my mind as to why it is legal, or survives even a cursory audit. Microsoft and OpenAI are clearly creating a circular flow of money, pretending it’s an investment, and letting OpenAI just set fire to it all:

That barely scratches the surface of the funny accounting in the AI bubble. Microsoft “invests” in Openai by giving the company free access to its servers. Openai reports this as a ten billion dollar investment, then redeems these “tokens” at Microsoft’s data-centers. Microsoft then books this as ten billion in revenue.

Nvidia does more or less the same thing with data centers, funding them with money that is paid back to them to purchase GPUs:

That’s par for the course in AI, where it’s normal for Nvidia to “invest” tens of billions in a data-center company, which then spends that investment buying Nvidia chips. It’s the same chunk of money is being energetically passed back and forth between these closely related companies, all of which claim it as investment, as an asset, or as revenue (or all three).

I thought this sort of circular shell-company thing was illegal? Apparently not, or at least not in these modern days when “illegal” is meaningless if it inconveniences oligarchs, monopolies, or friends of Trump.

Writing in Locus (Doctorow sometimes writes SF, so that’s a natural venue for him), he predicts how people will be forced into essentially bad jobs as mere assistants to LLMs that are nearly always wrong. ^[3] He uses some delightful jargon from automation:

• A centaur is when the human is on top, using the AI as an assistant (body of the horse).
• A reverse centaur is when the AI is in charge, forcing the human to fact-check every single thing it does, repetitively.

Summary: Centaur good, reverse centaur very bad.

(I was unable to track down the originator of this term; let me know if you do.)

Since LLMs are highly tuned to sound convincing, even when writing computer code, most of the stuff they write is very, very difficult to fact-check and debug. Assigning a human to wade through the slop looking for plausible but wrong bits is hopeless.

That will quickly collapse into low-paid, low-morale workers who don’t really bother to check on the AI slop: reverse centaurs.

There appears to be little we can do about this. We could just walk away from it, but given the obstinacy of our oligarchs, that is unlikely. The result will probably be an economic collapse, happening at a time when the US government is in a state of fascist collapse and the world careens to war on multiple fronts.

That will be very, very ugly.

As for what one might see next, Doctorow offered this advice to the head of LLM AI strategy at Cornell, for the university’s benefit as an institution:

Plan for a future where you can buy GPUs for ten cents on the dollar, where there’s a buyer’s market for hiring skilled applied statisticians, and where there’s a ton of extremely promising open source models that have barely been optimized and have vast potential for improvement.

AI isn’t going to wake up, become superintelligent and turn you into paperclips – but rich people with AI investor psychosis are almost certainly going to make you much, much poorer.

(Explanatory link about paperclippers added.)

So you might, in the best possible case, be able to pick through the rubble for parts to salvage. As a former “skilled applied statistician”, I’m glad I’m retired now. That’s all assuming you survive the intervening chaos.

So how close are we to a rise in unemployment, recession, or depression?

An article on Axios ^[4] tells us of the almost-alarming state of the Beveridge curve, shown here.

• This curve, popularized by British Economist William Beveridge in the 1940s, plots the monthly unemployment (presumably the more widely reported U3 in the US, not the more comprehensive U6?) on the horizontal axis and the number of job openings as a percent of positions total on the vertical axis.
  • When unemployment is low, we expect to see a lot of job openings being advertised (top left). Employers have trouble filling openings, because everybody’s already got a job, and thus openings pile up.
  • When unemployment is high, we expect to see very few job openings (bottom right), because people would immediately take those jobs.
• What the shape of the curve should be inbetween is the subject of much debate, and some nonlinear dynamics. It looks to me like a negative power law. But having been warned by the always amusingly informative Cosma Shalizi about the difficulty of power law fits ^[5], I won’t attempt it. (Hint: you can’t “just take logs” and expect anything to work! Also, many fat-tailed distributions are hard to distinguish from power laws unless you have huge amounts of data to sample the tails.)
• You want us to be on the upper left portion of the curve (blue/purple points): There, unemployment is low and employers can move their number of job openings up & down without affecting much of anything. Good times for workers, freedom to operate for employers.
• You do not want us to be in the lower right portion of the curve(reddish points): Here, unemployment is high. If employers lower the number of openings even just a little bit, then unemployment skyrockets further up.

As the article points out, the US is now (2025-Aug) at the knee in the curve. Will we go back up to the good part, or down to the right into the bad part?

Nobody knows.

But I really don’t like it.

The Weekend Conclusion

LLM AIs are sort of like the accordion/bagpipe hybrid skewered in this comic by Piraro: sounds inadvisable, like a generally bad idea that most people won’t like.

As it happens, I like bagpipe music, in the right place & time, especially when playing songs of the Second Jacobite Rebellion. (Yes, I am strange; are you only figuring this out now, 415 posts into this blog?) But I do not like the accordion, so the hybrid would still be bad, even for me.

More chillingly is the use of force by police to illustrate the cartoon. We have now altogether too much of that in the US, with Trump deploying national military and state guard forces to Democratic cities for the crime of not loving Trump enough.

Another AI Winter will come soon, and though it might be deserved this time for the LLMs, it will be bad. About 1/3 of the US stock market valuation is tied up in the “Magnificent 7”: tech companies that are, at this point, pretty much a bet on LLMs succeeding… somehow. A massive failure there, in these highly correlated companies, will likely take down much of our economy.

Doctorow explains, repeatedly, to plaintive questions from student that there just isn’t much you can do about it other than try to survive. Here’s what we’ve done Chez Weekend:

• We’ve revised our retirement investment portfolio to be less stock-oriented and less US-oriented.
• We’ve got Social Security and Medicare in place and working.
• We’ve recently gotten solar and batteries on our house in case of power grid disruption, and next week will pull the gas furnace in favor of a second heat pump. (More on that later, as we get some winter experience with the solar installation, in particular.)

I will be ecstatic if that turns out to be unnecessary.

(Ceterum censeo, Trump incarcerandam esse.)

Addendum 2025-Nov-17: Reverse Centaur

From Jamie McKelvie on BlueSky comes a perfect drawing of a reverse centaur:

Perfect. No notes.

Notes & References

1: C Doctorow, “Pluralistic: The real (economic) AI apocalypse is nigh (27 Sep 2025)”, Pluralistic blog 2025-Sep-27. ↩

2: B Merchant, “Blood in the Machine: The Origins of The Rebellion Against Big Tech”, Hachette Book Group, 2023. ISBN-13: 9780316487740. ↩

3: C Doctorow, “Commentary: Cory Doctorow: Reverse Centaurs “, Locus, 2025-Sep-01. ↩

4: N Irwin, “The worrying kink in this job openings, unemployment curve”, Axios, 2025-Oct-06. ↩

5: A Clauset, CR Shalizi, and MEJ Newman, “Power-Law Distributions in Empirical Data”, SIAM Review 15:4 (2009). DOI: 10.1137/070710111.

NB: Regrettably paywalled. The earlier pre-print is still available on arχiv.↩

Not Yet the Eschaton

As we’ve commemorated before (in 2020, in 2021, and in 2022) on this Crummy Little Blog That Nobody Reads (CLBTNR), today is the too-little-celebrated anniversary of the important day 1983-Sep-26 when the world could have ended, but did not. That was because one man disobeyed orders, and did some critical thinking instead.

It was particularly due to Russian Lt. Col. Stanislav Yevgrafovich Petrov (obituary from NPR at reference ^[1]), who wisely decided that, all else being equal, he would prefer not to destroy the world.

On that night, he was the duty officer at the Soviet nuclear early-warning center at Oko. Sunlight reflected off clouds had convinced a Soviet satellite watching a US missile base that exactly, and only, 5 missiles had launched. Petrov, on his own authority, defied the launch on warning standing orders and declared it a false alarm. Probably Petrov thought something like, “One missile, I can understand – that’s an accident. One thousand missiles, I can understand – that’s an attack. But five missiles? That I cannot understand.” Petrov stepped outside the box of obedience to standing orders, applied critical thinking, and decided not to cooperate with the system that would have ended the world.

Petrov rebelled; humanity got to live. It’s an excellent trade.

Sometimes a hero does not need to be brave to show heroism. Surprisingly often, critical thinking and a determination to do the right thing in the face of institutional decay is enough. Amid the rubble of our present-day institutional decay, we should all do likewise.

Some of us like to think of ‘Petrov Day’ as a not-yet-realized holiday that deserves more celebration.

The Weekend Conclusion

Pick your flavor of tikkun ha’olam. Whatever it is, do something that does not end the world, but instead heals it and contributes to the health of humanity.

When you find yourself also embedded in an absurd, evil system… do not obey. Especially do not obey in advance. Do the right thing instead.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: G Myre, “Stanislav Petrov, ‘The Man Who Saved The World,’ Dies At 77”, NPR: The Two-Way, 2018-Sep-18. ↩

What Has He Tried to Claim Now?

After the CDC ACIP vaccine fiasco, and amidst the continuing debacle of failing to release the Epstein files, the Trumpists need a distraction. RFKJr of course can be relied upon to supply controversial distractions at a moment’s notice.

He’s been teasing that he’ll tell us all what the cause of autism is, despite literally decades of evidence involving mostly genetics and a few environmental insults. Today was the day, when Trump (of course) seized the spotlight and announced that the New Correct Opinion in Trumpland was that use of acetaminophen (paracetamol/Tylenol) during pregnancy was somehow to blame.

CNN ^[1], for example, reports:

President Donald Trump announced Monday that the US Food and Drug Administration will notify doctors that the use of Tylenol during pregnancy can be associated with a “very increased risk of autism,” despite decades of evidence that it is safe.

Trump was unable to pronounce “acetaminophen”, despite offering medical advice on the subject. So he said the brand name “Tylenol” instead, a brand with an army of lawyers to defend it. That should be interesting to watch.

Not content with dispensing unqualified medical advice on a subject about which they know nothing, they proceeded to say the FDA will recommend leucovorin for the treatment of autism. Leucovorin is a high-dose calcium/folinic acid drug, typically used with cancer patients whose minerals are out of whack from chemotherapy.

The commercially branded version, Wellcovorin, was made by Glaxo-Smith Kline. However, since GSK stopped marketing it 27 years ago, the FDA withdrew approval. Now the FDA will be forced to re-approve it, with an indication for autism where it has never been tested.

Somewhat more disturbingly, there are generic versions of leucovorin (or its main ingredient) supplied by various unregulated or very lightly regulated supplement companies. They stand to make a bundle if there’s significant demand for leucovorin. Dr. Mehmet Oz, known as “Dr Oz”, is a wealthy, controversial, celebrity doctor, and now Trump’s administrator for the Centers for Medicare and Medicaid Services (CMS). He’s also a significant investor in iHerb ^[2], a California supplement company that sells the folinic acid part of leucovorin.

It stinks that the wildly weird recommended therapy is now something that will profit Trump people. Oz says he will divest, but in the Trump administration nobody divests.

CNN concludes with some real medical evaluation of their autism medical advice:

Dr. Arthur Caplan of the NYU Grossman School of Medicine Division of Medical Ethics called the announcement “the saddest display of a lack of evidence, rumors, recycling old myths, lousy advice, outright lies, and dangerous advice I have ever witnessed by anyone in authority in the world claiming to know anything about science.”

“What was said was not only unsupported and wrong but flat out malpractice in managing pregnancy and protecting fetal life,” he wrote in an email.

Sounds about right.

Let’s Consult the Science

AsapSCIENCE is a Canadian YouTube channel run by two people who are pretty good at explaining science with a dash of humor. (Occasionally one of them will be flamboyantly, performatively gay in a way that makes it all the more charming and hilarious. As in, a quote I half-remember: “Think of me as your cool gay science uncle.”) They are both qualified as actual scientists.

Here’s their latest video explainer on autism and acetaminophen:

• Autism is complicated, mostly genetic with implications for many genes.
• Acetaminophen has nothing to do with it.
• Any purported rise is due to better diagnostic tools and expanding of the criteria (to include adults, include Asperger’s, and so on – in the 60s, you basically had to be nonverbal to be considered autistic).

It’s a good summary for those of you who don’t want to wade through a paper.

But let’s face it: you know what kind of Crummy Little Blog That Nobody Reads (CLBTNR) this is. You wouldn’t be here if you didn’t want to wade through the relevant science papers. So the latest meeting of Some Weekend Reading Journal Club is now in session!

Our paper today is not only fully peer reviewed, but published in the prestigious Journal of the American Medical Association (JAMA).

It’s a big study by Ahlqvist, et al. ^[3] of a nationwide cohort of 2,480,979 children born in Sweden in 1995 - 2019 to 1,387,240 birthing parents. (Let’s hear it once again for the positive impact on research of universal health care and universal electronic medical records!)

• After filtering for one thing and another, as shown in the CONSORT flow diagram reproduced here, they had 185,909 children exposed to acetaminophen during pregnancy and 2,294,888 children who were not so exposed.
• They then diagnosed who among each group of children had a neurodevelopmental condition. In this particular study, that amounted to autism, ADHD, or intellectual disability.
• They first did a comparison between all the kids in each group, and then later did a genetics-sensitive comparison using only siblings that were exposed to acetaminophen vs not. (The latter will become important, anon!)
• The differences in rates between the acetaminophen vs no acetaminophen kids was measured, as is absolutely standard, with hazard ratios and their 95% confidence intervals.
  • First, the “hazard rate” is the probability that a certain event occurs, conditional on not occurring at a previous time. In this situation, it’s just the probability of a neurodevelopmental condition.
  • Second, the “hazard ratio”, or HR, is the ratio of the hazard rates between 2 groups. Here it’s the ratio of the probability of neurodevelopmental condition in the acetaminophen exposed group vs the non-acetaminophen group.
    • If HR > 1 then the acetaminophen group has a higher risk; if HR < 1 then it has a lower risk.
    • We then use statistics to get a 95% confidence interval on HR. To draw a statistically significant conclusion, we want either HR < 1 or HR > 1 and the 95% confidence interval all on the same side of 1. That is, we want to be 97.5% confident that the hazard ratio is on the side we think it is.

Now let’s consider Alqvist, et al.’s results, shown in the figure below.

• If the HR is to the left, it’s < 1 and the drug involved was protective against the problem. If it’s to the right, then the drug is a risk for the problem.
  • It’s only statistically significant if the error bar is wholly above or below 1.
• They considered separately the neurodevelopmental conditions of autism, ADHD, and intellectual disability.
• They computed HR and its 95% confidence interval for multiple kinds of groups:
  • Those exposed vs not exposed to acetaminophen, aspirin, non-aspirin NSAIDs (e.g., ibuprofen?), opioids (who takes opioids when pregnant?!), and antimigraine drugs.
  • They compared the exposed/non-exposed groups in the whole population, and then did a more refined comparison using only siblings in the same family who had been exposed/non-exposed.

The latter distinction, i.e., using matched sibling pairs only, is important. If you just look at the general population, you’re assuming there is no genetic component to the neurodevelopmental condition and thus exposure to the drug is the only relevant thing to measure. But we know, for example in autism, that genetics is a big factor! So by measuring between siblings, we control for genetics and ask if the drug was an additional risk factor, above and beyond genetics.

The latter is The Correct Question to be asking here.

Look at the first 2 lines in the figure (click to embiggen), which are the influence of acetaminophen on autism:

• The first line, showing the Hazard Ratio for the general population, is ever so slightly greater than 1: HR = 1.05 (95% CL: 1.02 - 1.08).

  This is what all the shooting is about!

• However, in the second line, we see the effect of controlling for genetics: HR = 0.98 (95% CL: 0.93 - 1.04).

  That is, the central estimate says acetaminophen is mildly protective against autism, though the error bar says it’s not statistically significant. In other words, there is no effect.

Result: There is no evidence whatsoever that associates acetaminophen with autism. Studies saying this are poorly controlled, failing to account for the known genetic component of autism. As shown here, when using siblings to control for genetics being the same on both sides, there is no effect.

Now look at the rest of the figure. In every single case, the result is the same! If there is a mild effect when doing a genetics-ignorant comparison of the whole population, the effect goes away when you do a proper sibling comparison.

The sole exception is near the bottom, considering the risk of aspirin for intellectual disability:

• The general population comparison shows a mild, not statistically significant risk. However, the genetically proper sibling comparison shows a statistically significant result that aspirin is protective against intellectual disability: HR = 0.71 (95% CL: 0.57 - 0.88).
• At the top of the chart, there’s a just-barely significant result showing aspirin is protective against autism too.

Interestingly – but unfortunately buried in the supplement – they did a test for dose-responsiveness of acetaminophen. If acetaminophen were really a cause, you’d expect high dose situations to produce a higher likelihood of autism, ADHD, or intellectual disability. This should show up in a hazard ratio that rises monotonically with dose.

This figure shows the hazard ratios as a function of acetaminophen dose. The blue bands are for the (bogus) population-wide comparison, and the pink bands are for the (properly genetics-controlled) sibling comparison. There is no meaningful, monotonic trend with acetaminophen dose. At all doses, the sibling comparison shows no effect at all, when genetics is properly taken into account.

Any acetaminophen/autism link is very, very thoroughly debunked!

Conclusions:

• This study is awesomely well powered, using essentially the entire population of Sweden over a period of 3 years.
• Acetaminophen, and pretty much everything else studied except aspirin (q.v.), is not associated with autism, ADHD, or intellectual disability.
• Anybody saying otherwise is doing a genetics-ignorant comparison, attempting to ignore the known strong genetic influence on those conditions.
• Checking for dose-responsiveness further rules out any association of acetaminophen with autism, ADHD, and intellectual disability.
• The single exception is favorable: aspirin looks mildly protective against autism and rather more strongly protective against intellectual disability.

The Weekend Conclusion

Summary: Yes, what they said is stupid.

Acetaminophen, during pregnancy or not, has nothing to do with autism. It has everything to do with Republican disdain for science, even for the very notion of evidence. (And, possibly, with making a corrupt profit for Dr. Oz; still waiting to see if he divests.)

And their desire to distract from their massive policy failures and destruction of democracy.

Don’t be distracted.

Here, as an instructive example, are the Weekend Publisher and the Assistant Weekend Publisher. (Given l’affaire Jimmy Kimmel, I thought I should consult with my publishers before offering an anti-Trump editorial opinion.) As you can see, they are not distracted by the latest Trump… emissions. In fact, they are not even much distracted from their nap schedule.

We should ignore the idiotic pronouncements, and keep up the grassroots political activity to throw out the idiots ASAP.

(Ceterum censeo, Trump incarcerandam esse.)

Addendum 2025-Sep-25: The APA Weighs In

The American Psychiatric Association is the oldest medical association in the United States, with more than 39,200 physician members specializing in the diagnosis, treatment, prevention, and research of mental illnesses.

Today the APA weighed in ^[4] with a reaction to the Trump’s & Kennedy’s weirdly stupid pronouncements on autism and acetaminophen (emphasis added):

“It is essential that the administration prioritizes evidence-based support for individuals on the autism spectrum and invests in long-term comprehensive research about the disorder.

Vaccines do not cause autism. Claims of any such association have been repeatedly discredited in peer reviewed studies.

Autism is a complex disorder, and it is incorrect to imply that a handful of studies have established causation. A strong base of evidence shows that acetaminophen, when taken as directed, is safe for use during pregnancy. Any decisions around a course of treatment should be determined by a patient and their doctor.

Leucovorin (folinic acid) has not been a recommended treatment for autism. It will require many more years of research before we know if leucovorin is an appropriate treatment for individuals with autism.

Autism spectrum disorders exist on a spectrum of neurodiversity. The country must focus its resources on expanding access to care and to building the evidence-base for future treatments.”

Summary:

• Vaccines don’t cause autism.
• Acetaminophen doesn’t cause autism.
• Leucovorin doesn’t treat autism.

Notes & References

1: J Christensen, B Goodman, M Tirrell, “Trump links autism to acetaminophen use during pregnancy, despite decades of evidence it’s safe”, CNN, 2025-Sep-23. ↩

2: K Plummer, “Will Dr Oz Benefit From Trump’s FDA Approving Leucovorin? What To Know”, Newsweek, 2025-Sep-23. ↩

3: VH Ahlqvist, et al., “Acetaminophen Use During Pregnancy and Children’s Risk of Autism, ADHD, and Intellectual Disability”, JAMA 331:14, pp. 1205-1214, 2024-Ap4-09. DOI: 10.1001/jama.2024.3172. ↩

4: APA Staff, “APA Statement on White House Announcement on Autism”, American Psychiatric Association News Releases, 2025-Sep-22. ↩

Huītzilōpōchtli & Moloch Continue Their Reign

Here on this Crummy Little Blog That Nobody Reads (CLBTNR), we’ve for some time been having… opinions about Ukraine. ^{[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14]}

It is, very regrettably, time for an update.

As we’ve been saying for a couple years now, we’re tracking the Russian casualty figures provided by the Ukrainian Ministry of Defence:

We’ve been using the Ukrainian Ministry of Defence’s figures for Russian casualties. Of course, one could object that they are a biased source. But when we looked at other sources, they were kind of in the middle of the pack. Some sources were wildly inflated, while others had extremely hard to believe small numbers. (The latter were institutions that insisted on a very high standard of evidence, like geo-location, identities, photographs, and so on. This leads to a very severe under-count, so people usually take their estimates and apply a multiplier derived… somehow.) The Ukraine MoD says they count, every day. That might even be true. But they seem reasonably credible compared to others, and they are the ones on the spot. So we’ll take their figures.

Sadly, it appears the Russians have now wasted the lives of another 100,000 of their young men for a total of 1.1 million so far in their invasion of Ukraine:

As we’ve previously remarked, this is continuing to blow a hole in Russian demographics of 18-44 year old males, i.e., those more or less qualified for military service. By our reckoning:

So 1.1 million dead is about $100\% \times 1.1 \mbox{million} / 23.7 \mbox{million} = 4.6\%$ of the military-age male population.

• Add to that reports that approximately 900,000 Russian men of military age have left Russia to avoid the draft.
• Then add that Russian casualties from COVID-19 seem to be around 400,000 ^[15]. Applying that to 1/2 the population to get males and then 1/3 to get those of military age means a loss of about an additional 67k men of military age unavailable due to being dead from COVID-19.

Together the Russian emigration and COVID-19 deaths give us about an extra million, for a total loss of about 2.1 million, or about 8.8% of the Russian men of military service age.

That’s… staggering. As we’ve quoted Bertrand Russell on this subject before:

“The mark of a civilized man is the capacity to read a column of numbers and weep.” – often attributed to Bertrand Russell, who said things like this if not exactly this, but would in any case almost certainly agree with the sentiment

When we look at the deaths in Russia’s invasion of Ukraine, the deaths in Israel’s invasion of Gaza, the wholesale dismantling of public health in the US in favor of superstition, summary military executions of people in boats in the Caribbean, and masked men kidnapping people from the streets of the US with no due process at all… it is arguable that we can no longer claim to be civilized. We are, perhaps, just clever barbarians?

We have let right-wing populism turn us into vicious, superstitious, and venomously racist savages. And somehow we have done this on a planet-wide basis.

Comparison Against Our Casualty Rate Model

Back in 2023, I started building a regression model tracking number of Russian casualties versus the number of days from the start of the invasion. By 2023-May-17, I’d updated the model a couple of times, and had 114 data points on the first 116 days of the war. At that point, I stopped updating in detail, because it was a lot of work to extract the data from the images posted on X/Twitter by the Ukrainian Ministry of Defence.

The model as of that date is shown here (click to embiggen). As you can see visually, the linear fit is pretty good. The casualty figures snake around a bit, sometimes above and sometimes below the line. But the fit is always pretty good, with nice tight confidence limits.

The statistics of the fit bear this out, showing an excellent $F$-statistic $p$-value for the overall fit and good $t$-statistic $p$-values for each coefficient. The adjusted $R^2 \sim 99.43\%$ is surprisingly excellent, i.e., the model was highly predictive.

Residuals:
    Min      1Q  Median      3Q     Max 
-3077.9 -1720.8    72.2  1169.4  3299.7 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.225e+05  3.318e+02   369.3   <2e-16 ***
x           6.996e+02  4.984e+00   140.4   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1767 on 112 degrees of freedom
Multiple R-squared:  0.9943,	Adjusted R-squared:  0.9943 
F-statistic: 1.97e+04 on 1 and 112 DF,  p-value: < 2.2e-16

The model back then showed a surprisingly steady casualty rate of about 700 ± 10 Russians/day.

That was at what turns out to have been just the beginning of this madness. One thing leads to another, and here we are having moved on from day 116 to approximately day 1000.

The plot here (click to embiggen) shows:

• the original data (blue points, lower left),
• the line fitted to the original data (black line, gray prediction confidence interval), and
• the new points, approximately every 100,000 deaths, plotted in red points.

The striking feature here is that when I started plotting the new (but sparse) points at about day 450, the death rate increased relative to the original model. If you squint diagonally back along the red points, there’s no argument any more for a nonlinear increase, but there is a very good argument for a linear increase, i.e., a new rate of deaths/day. (Yes, there are statistical tests of linearity/nonlinearity; no, I’m not going to bother.) We’ve gone from about 700 Russian deaths per day to a little over 1000 Russian deaths per day. That’s not a little thing: it’s a 43% increase in the Russian death rate!

If we were to re-fit a model, clearly it should have a breakpoint at 450 days, with separate linear fits before & after. (A scrupulously principled and honest approach would also fit where the breakpoint is, not impose it at 450 days.)

We don’t know if the Ukrainians have just gotten so much better at war (arguably true, especially with drones) or if the Russians have resorted to more and more human wave tactics (also arguably true). Either way, it’s more human sacrifice.

The Weekend Conclusion

Not all of this is the fault of the US or Europe, but we have certainly prolonged the conflict by being just… flighty about Ukrainian support.

On this matter as with so regrettably many others, all of us have much of which to be ashamed.

The treatment for shame is tikkun olam: repentance and repair of the damage we’ve all done to the world. But we certainly don’t seem interested in walking down that path, do we?

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: Weekend Editor, “Another Grim Anniversary”, Some Weekend Reading blog, 2023-Mar-02. ↩

2: Weekend Editor, “Do the Ukrainian Reports of Russian Casualties Make Sense?”, Some Weekend Reading blog, 2023-Apr-15. ↩

3: Weekend Editor, “Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-01. ↩

4: Weekend Editor, “Updated Update: Ukrainian Estimates of Russian Casualties”, Some Weekend Reading blog, 2023-May-09. ↩

5: Weekend Editor, “Updated${}^3$: Ukrainian Estimates of Russian Casualties Hit 200k”, Some Weekend Reading blog, 2023-May-17. ↩

6: Weekend Editor, “Ukraine Invasion: 250k Russian Dead”, Some Weekend Reading blog, 2023-May-17. ↩

7: Weekend Editor, “Tacitus in Ukraine”, Some Weekend Reading blog, 2023-May-25. ↩

8: Weekend Editor, “Casualties in Ukraine: Grief Piles Higher & Deeper”, Some Weekend Reading blog, 2024-Apr-10. ↩

9: Weekend Editor, “Post-Memorial Day Thought: 500k Russian Dead in Ukraine “, Some Weekend Reading blog, 2024-May-31. ↩

10: Weekend Editor, “Ukraine: 600k Russian Dead”, Some Weekend Reading blog, 2024-Aug-27. ↩

11: Weekend Editor, “Ukraine War: 700k Russian Dead”, Some Weekend Reading blog, 2024-Nov-04. ↩

12: Weekend Editor, “Ukraine War: 800k Russian Dead”, Some Weekend Reading blog, 2025-Jan-08. ↩

13: Weekend Editor, “Ukraine War: 900k Russian Dead”, Some Weekend Reading blog, 2025-Mar-21. ↩

14: Weekend Editor, “Ukraine War: 1,000,000 Russian Dead?!”, Some Weekend Reading blog, 2025-Jun-12. ↩

15: E Mathieu, et al., “‘Coronavirus Pandemic (COVID-19)’, Our World in Data”, Our World in Data, retrieved 2025-Sep-22. ↩

Where is the Font of US Political Violence?

Recently, with the murder in the US of far-right agent provocateur Charlie Kirk, we’ve been paying slightly more attention to domestic political violence. Predictably, the right-wing decided the source was leftists, minorities, and trans people. Within a day, historically black colleges and universities were under lockdown.

Then it came out that he was murdered by an even further right-wing white young man. But the blaming of the left did not stop. Consider a recent statement by JD Vance – the Vice President – in which he makes the expected fascist plea for purity, saying “there can be no unity with the left”, and claims violence comes mostly from the left:

Ok… is he lying or not?

At some point, we have to have updated our priors so that when a highly-placed Trump administration official says something, the baseline assumption should be that they are lying. However, we can, somewhat tiredly, fact-check this sort of thing… again.

Checking the Facts

First, it’s important to recognize that gaslighting on this subject is a long-term tradition on the American right. For example, consider the AP report on the Heritage Foundation’s claim that most violence comes from the left. ^[1] The opening is pretty clear:

WASHINGTON (AP) — The leader of a conservative think tank on Thursday misrepresented partisan differences in political violence in the United States, wrongly suggesting that people associated with left-wing causes commit more violence than those on the right.

This was in response to his remarks earlier in which he said,

… the country was in the midst of “the second American Revolution, which will remain bloodless if the left allows it to be.”

That is, of course, itself a threat of violence: either you let us dismantle America and build fascism, or we will meet your opposition with violence.

Study 1: Jasko, et al. in Proceedings of the National Academy of Sciences

Now, the AP article does devolve into the usual journalistic preoccupation with story, in which they cite numerous examples. However, before that they sensibly cite research from 2022 on the comparative sources of political violence in the US published in the prestigious PNAS. ^[2]

Jasko, et al. tried to see if there was a different propensity to political violence among left-wing, right-wing, and Islamist extremists. They had 2 large datasets of violent events along with various covariates like education and social status, of which the relevant one for today is the one for the United States: the Profiles of Individual Radicalization in the United States (PIRUS).

• This includes 1,563 individuals involved in right-wing, left-wing, or Islamist violence.
• The time period covered was 1948 - 2018.
• 90% of the subjects were male, with mean age 35 years.

Right away in Table 1, there’s a tell: the breakdown of entries is 17.6% Islamist, 23.4% left-wing, and a whopping 59% right-wing. It sure looks like, just from the record, that most political violence has been right-wing.

They first used the MICE method (“multivariate imputation through chained equations”) to impute missing data. Then they did some multivariate logistic regression, estimating the log odds ratio of violence based on ideology and numerous correcting covariates like education, marriage, gender, immigration, military experience, and so on.

These covariates are important, because they allow you to consider ideology separately: if one ideology is better educated and less violent, then is the lessening of violence due to education or ideology? By regressing on all such variables, they (partially!) correct for this.

A word about coding: it’s natural to think about the ideology variable here as ternary, i.e., left/right/Islamist. But the way these things work in analysis is you want binary variables. So there’s this thing called dummy coding. There’s a “Left” variable that’s 1 for leftists, else 0; there’s an “Islamist” variable that’s 1 for Islamists, else 0. There’s no particular variable for “Right”, because that’s implied when both “Left” and “Islam” are 0. That is to say: “Right” is the baseline level, and everything is what’s called a contrast with respect to baseline. (This is utterly standard procedure.)

So their model looks something like (intuited by your humble Weekend Editor, since they have no equations in their paper):

If $\beta_i \ll 0$, then the associated variable $i$ is protective against violence. Their results, from Table 2:

• Left-wing is protective against violence ($\beta \sim -1.70$, $p \lt 10^{-3}$), Islamist is more or less insignificant. Thus right-wing is implicated. (it would have been more dramatic if this level hadn’t been obscured by dummy-coding.)
• Other statistically significant protective variables: being an immigrant, being white, and being in the first decade of the 2000s. NB: Contrary to all the right-wing talking points, immigrants are less violent.
• Other statistically significant pro-violence variables: previous criminal experience, and being in the 1970s or 1980s.

So my reading of their table is that the typical domestic terrorist is a non-immigrant right-winger with previous criminal experience. Let’s see what their interpretation is, from the paper (emphasis added):

When compared to individuals associated with a right-wing ideology, individuals adhering to a left-wing ideology had 68% lower odds of engaging in violent (vs. nonviolent) radical behavior (b = −1.15, SE = 0.13, odds ratio [OR] = 0.32, P < 0.001). On the other hand, the difference between individuals motivated by Islamist and right-wing causes was not significant (b = 0.05, SE = 0.14, OR = 1.05, P = 0.747). Expressed in terms of predicted probabilities, the probability of left-wing violent attack was 0.33, that of right-wing violent attack was 0.61, and that of Islamist violent attack was 0.62. These findings remained robust after we controlled for demographic variables (sex, age, education, minority status, immigration status), prior criminal experiences, military experience, and decade in which the perpetrator entered the database. Of the control variables, immigrants were less likely to engage in violence. Those who had a prior violent criminal record were more likely to engage in violence. Further, older individuals and those identified as white were less likely to engage in violence in this sample. Finally, when contrasted with the 2010s, persons whose date of exposure was in the 1970s and 1980s were more likely to be violent and those in the 2000s were less likely.

Their conclusion is clear, even so much that it’s stated right up-front in the abstract:

… we find that radical acts perpetrated by individuals associated with left-wing causes are less likely to be violent. In the United States, we find no difference between the level of violence perpetrated by right-wing and Islamist extremists.

Yes, you read that correctly: left-wing violence is less likely, but right-wing violence is indistinguishable from Islamic terrorism.

So far, it looks like Vance is deeply, horribly wrong about both leftists and immigrants. The real sources of US political violence are native-born right-wingers.

Ok, But… What Else Ya Got?

Now, you might object that that’s just one study (though it is over multiple decades and uses the best datasets known… still, just one). Thomas Aquinas was alleged to have said “hominem unius libri timeo”, or “I fear the man of one book.” ^[3]

So, by all means, let’s find another study. Or two. Or… more? Just to be sure, you know. AP fact checkers led us to the Jasko, et al. paper in PNAS above, so that’s 1 study.

Study 2: Alex Nowrasteh at the Cato Institute

Now, maybe you’re a Republican thinking I’m some pointy-headed, academic-loving, liberal intellectual. You are correct. Though, really, that’s less of an insult than you might think. So let me find a more conservative source for you.

How about the Cato Institute? It’s a self-styled “libertarian think tank”. True, they like to distinguish that from “conservative”, but from my end of the political spectrum a libertarian is just a conservative obsessed with economic bullying and an Ayn Rand fetish.

So you can’t accuse me of citing only friendly sources with this one!

Consider the analysis of Alex Nowrasteh, currently their vice president for economic and social policy studies. Writing on his site with David Bier ^[4], Nowrasteh has analyzed a different set of data on politically motivated terrorist killers.

Sadly, he opens by repeating uncritically the conservative canard that Kirk was murdered by a leftist:

People are apprehensive about these attacks in the wake of the assassination of Charles Kirk by a left-wing, politically motivated terrorist.

In fact, the alleged killer appears to be an even further right-wing nut. But let’s just take this as a credential that Nowrasteh is deep into the right-wing culture and can in no way be accused of being sympathetic to my views.

Now, he’s assembled a number of interesting datasets on terrorist attacks in the US, their political motivators, and the resulting casualties. While he did not do a deep statistical analysis like the missing data imputation and logistic regression of Jasko, et al. above, he did make a very nicely done graphic, shown here. (Click to embiggen.)

He’s broken down the politically motivated killings by ideology (columns) and by 5-year periods (rows). Consider the first 2 columns, the number of murders committed by left and right ideologues.

It is blunt trauma obvious that, over the last half-century, the right has been responsible for almost all the political violence in the United States.

And today you learned that from the Cato Institute.

Study 3: The National Institute of Justice Report on Domestic Terrorism

The US government’s National Institute of Justice published a study of domestic terrorism on 2024-Jan-04 ^[5] on the web site of the Office of Justice Programs (ojp.gov).

In a perfectly on-brand move, the Trump administration immediately disappeared the report from the Office of Justice Programs web site, apparently just after the Kirk killing. (I didn’t fact-check the date they disappeared it, but just noted the coincidence that it was gone when I wanted it the most.)

We can see why they want the report to be buried. It gets directly to the point in the first paragraph (emphasis added):

Militant, nationalistic, white supremacist violent extremism has increased in the United States. In fact, the number of far-right attacks continues to outpace all other types of terrorism and domestic violent extremism. Since 1990, far-right extremists have committed far more ideologically motivated homicides than far-left or radical Islamist extremists, including 227 events that took more than 520 lives.[1] In this same period, far-left extremists committed 42 ideologically motivated attacks that took 78 lives.[2] A recent threat assessment by the U.S. Department of Homeland Security concluded that domestic violent extremists are an acute threat and highlighted a probability that COVID-19 pandemic-related stressors, long-standing ideological grievances related to immigration, and narratives surrounding electoral fraud will continue to serve as a justification for violent actions.[3]

They go on to talk about the apparently-excellent PIRUS database, used by Jasko, et al. above. They funded a similar effort to study hate crimes in the US, creating a similar database, called BIAS (966 individuals, from 1990 to 2018). That revealed a startling fact, that political violence and hate crimes based on race or sexual orientation are deeply related (emphasis added):

Furthermore, the PIRUS and BIAS data reveal that U.S. extremists and individuals who commit hate crimes are often motivated by overlapping views. For instance, it is common for individuals from the anti-government militia movement to adopt views of white supremacy or for those from the extremist environmental movement to take part in anarchist violence. Nearly 17% of the individuals in PIRUS were affiliated with more than one extremist group or sub-ideological movement, and nearly 15% of the individuals in BIAS selected the victims of their hate crimes because of multiple identity characteristics, such as race and sexual orientation.[12]

So, according to the government’s own research, most violence in the US is related to right-wing ideology and white supremacy. And it’s hard to distinguish those any more.

Study 4: The Economist on the Prosecution Project’s Data

Next, let’s consider The Economist.

This is no left-wing rag: it’s a British centrist publication, generally centrist to slightly right of center. In Wikipedia’s description, it is described as more or less appealing to the economic elite’s modern neo-liberal preferences:

The newspaper typically champions economic liberalism, particularly free markets, free trade, free immigration, deregulation, and globalisation. Its extensive use of word play and high subscription price has linked the paper with a high-income elite readership, drawing both positive and negative connotations. In line with this, it claims to have an influential readership of prominent business leaders and policy-makers.

So, again: very clearly not appealing to my own preferences here, but looking for wide support even from those who disagree with me.

In an unattributed but otherwise excellent article on 2025-Sep-12 ^[6], they ask if “radical-left” violence is really on the rise in the US.

To get at this question, they use data from the Prosecution Project of Michael Loadenthal at the University of Cincinnati. That project analyzes felony criminal case records for ideological motivations. They comb over criminal complaints, indictments, and court records, looking for, in Loadenthal’s words, those seeking “a socio-political change or to communicate” to outside audiences.

The results are shown in the bar chart reproduced here (click to embiggen). The conclusion is obvious that most of the violence is right-wing (in red). But don’t just trust my interpretation, listen to what The Economist says (emphasis added):

Its data show that extremists on both left and right commit violence, although more incidents appear to come from right-leaning attackers (see chart 1).
…
One paper by Celinet Duran of the State University of New York at Oswego studied political violence between 1990 and 2020. It found that there were far more frequent and deadly attacks by the hard-right than the hard-left, although left-wing violence increased throughout the study period. A separate tally by the Anti-Defamation League, an advocacy group, shows that 76% of extremist-related murders over the past decade were committed by those on the right.

Indeed: “see chart 1”.

Right-wingers are obviously and provably the source of US political violence.

Study 5: Phillip Bump on the Anti-Defamation League’s Data

Now consider the work of Philip Bump, a former Washington Post columnist. (The WaPo offered him a buyout on 2025-Jul-17, so he left in a part of the sad, mass exodus that includes other luminaries such as Jonathan Capehart.)

Bump used to write a weekly newsletter called “How to Read This Chart”, which warms my flinty old scientist’s heart. Most scientists figure they’re done with a figure when it’s draw: “I drew you a picture. Do I have to explain it too?!” Yes. Yes, you do! Every time I made a scientific presentation, each figure was accompanied by a paragraph explaining what it was (in line with the admirable instructions of Arlo Guthrie in Alice’s Restaurant.).

Bump’s analysis ^[7] neatly summarizes some work from the Anti-Defamation League on extremist killings by year (previously analyzed by Bump for a WaPo column ^[8]), summarized in the chart shown here (click to embiggen). Right-wing is shown in pink, left-wing in light blue, domestic Islamist extremist in purple, and anything else in gray.

Note the sea of pink, sustained over a decade.

Bump goes on to cite the now-suppressed NIJ report we also used above (emphasis added):

Militant, nationalistic, white supremacist violent extremism has increased in the United States. In fact, the number of far-right attacks continues to outpace all other types of terrorism and domestic violent extremism.

How many times are we going to have to say “see chart 1” until it’s obvious?

Apparently a lot more, sadly.

Study 6: USAFacts on US Government Data on Red State Homicide Levels

You might argue that the above is all limited to just politics, and that right-wingers are not especially violent about anything else. That’s not much better, but it’s something. So let’s look at general violence and ideology.

For that, we turn to USAFacts, which bills itself as writing “explainers” for government data that other people might find hard to access and understand. I haven’t dealt with them a lot, but they seem legit on the surface.

On 2025-Sep-09 they published an article using CDC data to examine the homicide rate across states. ^[9] Looking at the rate per 100,000 people, the top 5 and bottom 5 of the list are:

• Highest murder rates: Mississippi, Louisiana, Alabama, New Mexico, Tennessee.
• Lowest murder rates: New Hampshire, Utah, Rhode Island, Massachusetts, Idaho.

I really should do a regression of the murder rate on the Trump percentage margin in each state. But… we’re 6 studies in and my energy is starting to flag.

So we will simply note that:

• the highest murder states are relentlessly southern and red, with an exception for New Mexico which is one of the poorest blue states, while
• the lowest murder states are mostly northern and blue, with exceptions for the highly Mormon populations of Utah and Idaho.

One could argue that southern culture in the US has a much more violent streak to it. One could argue that those states have populations that skew younger, with poorer impulse control.

But they are red states, and they are more violent.

Study 7: Red States Less Free, More Poor, Shorter Lives

Christopher Armitage is an Air Force vet who now consults in security, disaster preparedness, and human trafficking.

He’s written a deeply researched article on how social policy in red states influences not just social freedom, but medical care, prosperity, and lifespan. ^[10] He looks across states with at least 8 years of consistent control by one party or the other (i.e., a trifecta: both houses of the state legislature and the governorship).

There’s a lot there, especially in his references. So let’s just look at a couple summary comparison paragraphs:

• Freedom:

  Let’s examine what freedom actually means in red states. In Texas, the government forces women to carry dead fetuses to term.¹⁴ Women have died from this. In Florida, the state investigates parents who support their trans children.¹⁵ In Tennessee, you can be fired for being gay.¹⁶ In Alabama, librarians face prison for having the wrong books.¹⁷
  …
  Meanwhile, in blue states, consenting adults can marry, adopt, and live without fear.¹⁶ Women make their own reproductive healthcare decisions.¹⁴ Trans people receive medical care.¹⁵ You can read any book you want.¹⁷ You can smoke marijuana without becoming a felon.¹⁸ You can vote easily with early voting and mail ballots, because that’s what happens in free democracies.¹⁹

• Poverty:

  Texas has the second largest economy in America. Florida has the fourth. These aren’t poor states, they’re economic powerhouses that choose to let their people suffer. Texas, despite its trillion-dollar economy, maintains the highest uninsured rate in the nation at 18.8%. Florida, despite massive budget surpluses, ranks 44th in healthcare access and has the most regressive tax system in America.
  …

  Meanwhile, Vermont, with an economy smaller than Corpus Christi’s, provides near-universal healthcare coverage. Maine, with half of Florida’s GDP per capita, achieves better education outcomes. New Mexico, despite being one of the poorest blue states, still manages lower maternal mortality than wealthy Texas.
  …
  This isn’t about money. It’s about choices. Red states with plenty of money choose to spend it on corporate tax breaks instead of keeping mothers alive. They choose to ban books instead of fund schools. They have the resources to match Massachusetts’ outcomes tomorrow. They simply choose not to.

• Lifespan:

  Democratic states own the top of the life expectancy rankings. Hawaii leads at 79.9 years, followed by Massachusetts, Connecticut, and New York.¹ Republican states own the bottom. Mississippi’s 70.9 years ranks dead last, followed by West Virginia, Alabama, Louisiana, and Kentucky.¹

  This isn’t bad luck or geography. It’s what the Republican party wants for it’s constituents.

  Texas has the highest uninsured rate in America at 18.8%.³ Massachusetts has the lowest at 2.9%.³ Every single state that refused to expand Medicaid has a Republican trifecta.⁴ The result? People die from treatable diseases.

  Maternal mortality tells the same story. Louisiana kills mothers at 58.1 deaths per 100,000 births. Georgia follows at 48.4, then Indiana, Arkansas, and Alabama, all Republican strongholds.⁵ Massachusetts loses just 17 mothers per 100,000 births. California loses even fewer.⁵

Basically the Democratic trifecta states pursue policies that lead to more freedom, less poverty, and longer, healthier lives. Republicans choose not to do this, in what amounts to self-inflicted wounds.

The Weekend Conclusion

So there are 7 studies, from “pretty good” to “excellent”, presenting you with sufficient facts to see that Vance is either ignorant or lying. (And that’s just what I was able to find and read in a single afternoon: “vest pocket scholarship”, where I looked no further than my own vest pockets!.)

There is a slim possibility that Vance is just simply ignorant, and can’t be bothered to learn the facts. But much more likely, Vance is lying.

Of course he is lying: the violence almost always comes from his side, and it would be politically inconvenient for him if you knew that fact.

The most important fact for you to learn: is that the fascists cannot be bothered to learn the facts.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: D Klepper & F Amiri, “FACT FOCUS: Heritage Foundation leader wrong to say most political violence is committed by the left”, Associated Press, 2024-Jul-18. ↩

2: K Jasko, G LaFree, J Piazza, MH Becker, “A comparison of political violence by left-wing, right-wing, and Islamist extremists in the United States and the world”, Proceedings of the National Academy of Sciences, 119:30, e2122593119, 2022-Jul-18. DOI: 10.1073/pnas.2122593119. ↩

3: He might have meant that he feared the focused knowledge of a specialist that might be turned against him, or he might have feared the semi-literate ignorance of someone who is at best partially informed from only a single source. We’re going with the latter, here: “Beware the man of 1 study.” ↩

4: A Nowrasteh, “Politically Motivated Terrorist Killers”, Laissez-Fair, Laissez-Passer blog, 2025-Sep-13.

The source for the plot above and the underlying data is also available here. ↩

5: S Chermak, et al., “What NIJ Research Tells Us About Domestic Terrorism”, National Institute of Justice Journal 285, 2024-Jan-04.

NB: Shortly after the Kirk assassination, the Trump administration without explanation disappeared this report from its usual home at the web site of the Office of Justice Programs (ojp.gov). The link above goes to an archival copy. You may have to pause your VPN to get it to work.

Just in case that also goes away, we’ve archived a PDF of it here on this Crummy Little Blog That Nobody Reads (CLBTNR). ↩

6: Economist Staff, “Is “radical-left” violence really on the rise in America?”, The Economist, 2025-Sep-12.

NB: Regrettably paywalled. An archival copy may be read here. ↩

7: P Bump, “Reassessing the ‘fine people hoax’ hoax”, pbump.net blog, 2025-Sep-12. ↩

8: P Bump, “Underrecognized: Extremist murders are usually from right-wing actors”, Washington Post, 2023-Feb-28.

NB: Regrettably paywalled. An archival copy may be read here. ↩

9: USAFacts team, “Which states have the highest murder rates?”, USAFacts.org web site, 2025-Sep-09. ↩

10: C Armitage, “Red States: Less Freedom, More Poverty, Shorter Lives”, The Existential Republic blog, 2025-Sep-05. ↩

You Have to Get Out Ahead of the Crazies

Normally, I’d say get both the flu and COVID-19 shots sometime early in October, so immunity would peak in the middle of winter. Right now, mid-September, is a bit early. Why the rush?

Because Kennedy and his new ACIP crew, packed with unqualified people, are forming up to withdraw the vaccinations completely. The WaPo ^[1] and Ars Technica ^[2] report:

Trump health officials plan to link coronavirus vaccines to the deaths of 25 children as they consider limiting which Americans should get the shots, according to four people familiar with the situation who spoke on the condition of anonymity to describe confidential information.

They apparently plan to do this at the 2025-Sep-18 meeting of the CDC’s Advisory Committee on Immunization Practices. Kennedy recently fired the ACIP members, replacing them with unqualified people more to his liking. They will have in their power to revoke recommendations and insurance coverage for the vaccines, as well as ask the FDA to ban the medications altogether.

The data they’re using is from the Vaccine Adverse Event Reporting System (VAERS, though really the “R” should stand for “Rumors”). The thing to know about VAERS: nothing in it is verified! Literally anybody can enter their story and claim it’s vaccine-related. (Why does that even exist? Sort of an early warning system, to tell you to go look at other data to see if it’s real, and no more than that.)

Four unnamed sources close to the situation told the Post that Trump administration health officials appear to be using information from the Vaccine Adverse Event Reporting System (VAERS) to make the claim that COVID-19 vaccines have killed children. VAERS is a system in which anyone can report anything they think is an adverse event related to a vaccination. The reports are completely unverified upon submission, and the Centers for Disease Control and Prevention staff follow up on serious reports to try to substantiate claims and assess if they were actually caused by a vaccine. They rarely are.

So… vibes, basically.

This is… alarming.

And it’s not just alarming to me, but also to epidemiologists and physicians. Witness the reaction to epidemiologist Elizabeth Jacobs from a physician and clinical virologist:

Ok, that’s enough for me to act! I scheduled an appointment this very day. (The Weekend Editrix is, alas, in Japan now. When we video this evening, I’ll beg her to get a booster in Japan.)

What’s mNEXSPIKE?

Upon scheduling the appointment, I was informed that since I was over 65, I’d be getting the Moderna “mNEXSPIKE” vaccine. ^[3] Apparently this is a new and different thing for elders and those at higher risk for severe COVID-19, so let’s find out what it is.

We’ve known for some time now that the Moderna and Pfizer vaccines are not just straight-up RNA sequences from the virus, but are particularly engineered to replicate fast and stimulate deep immune reactions. We’ve even analyzed, on this Crummy Little Blog That Nobody Reads (CLBTNR), those sequences to find about 11 different biohacks that were applied to the sequences. ^[4]

So it should come as no surprise that this has continued. ^{[5] [6]}

• Recommendation: It’s recommended for those over 65 or age 12-64 with at least one underlying condition that means COVID-19 would be especially bad news. It apparently induces even stronger immunity than the Moderna SPIKEVAX, q.v., so it’s appropriate for elders whose immune systems need stronger provocation.
• Design: Rather than reproduce (an engineered form of) the whole spike protein, it just contains 2 domains of the protein: the N-terminus domain and the receptor binding domain.
  • Proteins are made up of a chain of amino acids, and the way they fit together means you’ve got a nitrogen hanging off one end (N) and a carbon off the other (C). For the SARS-CoV2 spike, the N-terminus domain is involved in sticking to the target cell for infection.
  • The receptor binding domain is what binds to a receptor (ACE2, I think?) on the cell surface to get itself inside the cell.
  • Obviously those 2 areas of the protein are crucial for infection, and they’re where most antibodies tend to bind anyway. So mNEXSPIKE concentrates on just those areas.
• Dose: One of the reasons I’ve liked Moderna is that it’s dosed higher than Pfizer. Here with mNEXSPIKE, though, the dose goes down (50μg for SPIKEVAX vs 10μg for mNEXSPIKE). That’s because it induces such a stronger immune reaction, you just need less of it.

• Clinical trials: The Phase 3 NextCOVE study (NCT05815498, 11,454 persons) compared mNEXSPIKE with SPIKEVAX, head-to-head.

  The goal was to demonstrate “noninferiority”, i.e., get at least as good efficacy, and in fact get the lower 95% confidence limit of the efficacy difference between mNEXSPIKE and SPIKEVAX to be above -10%. That is, you want to see more efficacy from mNEXSPIKE, and you want to be very sure that the worst case is not too bad.

  • That goal was met: mNEXSPIKE has 9.3% (99.4% CI, -6.6, 22.8) higher relative vaccine efficacy relative to SPIKEVAX.
  • Specifically in seniors, it was even better: 13.5% [95% CI, -7.7, 30.6].
  • It also induced higher seroresponse rates and geometric mean neutralizing antibody titers.

So… yeah, this looks really, really good.

The Vax Experience

So here we are, at our local pharmacy, at the appointed hour for a same-day appointment. (And for that, I’m grateful.)

As you can see, they did indeed trot out the mNEXSPIKE version of the Moderna vaccine for your humble Weekend Editor. It amazes me that we’ve gotten so good at engineering mRNA sequences for immune stimulation that you only need to give me 10μg IM to drive my aging immune system into staying on guard for the next 6 months.

And, as is now a CLBTNR tradition, here is my portside dorsal manipulator tentacle, dutifully and gratefully receiving the jab. By my count, that is my 11th COVID-19 shot, since starting way back in March of 2021.

Mission thus having been accomplished, I picked up a gyro/veggie/rice plate from a deli on the way home. Probably not gonna feel like cooking dinner tonight, and that’s fine.

The Weekend Conclusion

The Weekend Editrix is currently in Japan. I’ll have to ask her to ask around about the availability of the 2025-2026 COVID-19 booster there before she returns to the US.

Get yourself covered now, while it’s still possible.

As always, with COVID-19 vaccination blog posts, tune in tomorrow to hear about the (generally minor) side effects.

(Ceterum censeo, Trump incarcerandam esse.)

Addendum 2025-Sep-14: Sequelae

So here we are, 24 hours later.

The vaccine mNEXSPIKE is advertised as provoking a stronger immune reaction (so it’s given at a lower dose). And yes… yes, it does indeed do that. I had a somewhat difficult night, with about 1.5°C fever, extreme fatigue, and a headache that strobed every time I coughed. But, honestly, it was not as bad as getting a mild case of the flu.

And by this afternoon it’s not entirely cleared up, but well enough. And I can take some ibuprofen. It’ll be fine.

Absolutely worth it. I so very much look forward to not getting COVID-19 this winter.

You should, too.

Addendum 2025-Sep-20: ACIP Results

So, the CDC’s Advisory Committee on Immunization Practice finally met.

It was, in the words of one epidemiologist, a “goat rodeo”:

• They tried to rebunk the thoroughly debunked “turbo cancer” anti-vax conspiracy theory that mRNA vaccines somehow cause cancer.
• They tried to promote the exceptionally stupid proposition that COVID-19 vaccines cause “… changes in the immune system that cause other infections, autoimmunity, chronic inflammation, immune tolerance and impaired immune surveillance including immune fatigue or suppression.”
• They tried to say it caused multiple child deaths, using unverified VAERS reports that did not check out anywhere else.
• They subjected CDC scientists to the verbal equivalent of waterboarding, with questions that were wildly inappropriate, irrelevant, and disrespectful. (Like: “If a hippopotamus appeared in your lab…”)
• They listened to presentations from people with highly suspicious histories, such as El-Deiry, who has 75 of his publications flagged on PubPeer for data irregularities.
• They tried to blame Long COVID on vaccines, despite evidence saying the exact opposite (not to mention that most cases of Long COVID date from before the vaccines were available).
• They tried to impose a requirement for a prescription (just barely failed, on a 6-6 tie vote).
• When that failed, they imposed a requirement for “shared clinical decision making” with a healthcare provider.
  • An interesting loophole: a pharmacist counts, so if you ask a pharmacist for a vaccination, the requirement is met!
  • Interestingly, given the requirement for younger people to have a medical need, the Michigan Chief Medical Executive declared that not having the latest vaccination was itself a condition that constituted sufficient medical need to justify getting the latest vaccination. It’s come down to that, apparently.

In general, they entertained arrant nonsense, disinformation and outright lies, while showing little to no understanding of the principles of public health.

Still… they did not pull the authorization, so the vaccines are still available. While the “consultation with a health care practitioner” will almost surely be abused in red states to throw up barriers, at least the rest of us should not have too much problem getting vaccinated.

Still, I’m glad I got it done before the “goat rodeo”. And I’m glad the Weekend Editrix will be able to get it upon her return from Japan.

Notes & References

1: LH Sun, R Roubein, D Diamond, “Trump officials to link covid shots to child deaths, alarming career scientists”, Washington Post, 2025-Sep-12.

NB: Regrettably paywalled; see archive version here. ↩

2: B Mole, “RFK Jr.’s CDC may limit COVID shots to 75 and up, claim they killed kids”, Ars Technica, 2025-Sep-12. ↩

3: Moderna Staff, “mNEXSPIKE, A NEW COVID-19 VACCINE “, Moderna web site, downloaded 2025-Sep-13. ↩

4: Weekend Editor, “Reading the RNA in the Pfizer & Moderna vaccines”, Some Weekend Reading blog, 2021-Apr-08. ↩

5: D Ernst, “FDA Approves Moderna’s Next-Generation COVID-19 Vaccine mNexspike”, Vaccine Advisor, 2025-Jun-11. ↩

6: Medical Letter Staff, “COVID-19 Update: mNEXSPIKE — A New Moderna mRNA Vaccine for COVID-19”, Med Lett Drugs Ther 67:1733, pp. 119-20, 2025-Jul-21. DOI: 10.58347/tml.2025.1733h. ↩

General Matters

You might recall that it’s been a custom on this Crummy Little Blog That Nobody Reads (CLBTNR) that we live-blog the FDA VRBPAC advisory sessions on COVID-19 vaccines. We did not do that starting this year, since we have little tolerance for the Trump/Kennedy willful disregard of science. You can see here ^[1] why we felt the need to disengage from the venomous nonsense.

Still, let the record show that the FDA VRBPAC met on 2025-May-22, and recommended a monovalent booster based on the JN.1 lineage, preferably LP.8.1 (though I think Novavax can be JN.1, since they’re a protein vaccine and can’t pivot fast) ^[2]:

Based on the totality of the evidence, FDA has advised the manufacturers of the approved COVID-19 vaccines that to more closely match currently circulating SARS-CoV-2 viruses, the COVID-19 vaccines for use in the United States beginning in fall 2025 should be monovalent JN.1-lineage-based COVID-19 vaccines (2025-2026 Formula), preferentially using the LP.8.1 strain.

That’s… ok, I guess?

But it’s not great: we’re still, as always, several variant strains behind reality. The virus mutates faster than our systems can respond, especially now with all the right-wing foot-dragging and imposition of nonsensical constraints.

For example, let’s consider the wastewater genomics of SARS-CoV2 collected over the years by the Wisconsin State Laboratory of Hygiene. ^[3] First a couple of terms:

• Metagenomics is when you do gene sequencing on something other than cells, to see what all the things living there are. For example, this has been done on seawater and revealed a host of bacterial and viral beasties that were poorly understood.
• Wastewater metagenomics is when you do this at a sewage processing plant. Actually, all sorts of analyses are done on sewage, because of its startling honesty: everybody who uses a toilet contributes. You can tell a lot about cocaine use, for example, by looking for the by-products. Doing metagenomics, specifically focused on the SARS-CoV2 genome, is a way to tell which strains are in circulation with a very high level of honesty not relying on anybody reporting anything. (Unless use of a toilet constitutes reporting, in which case I really don’t want to hear about your theory of “reporting”.)

This has been a big deal for some time with COVID-19; we’ve been writing enthusiastically about it in this CLBTNR for some years now. ^{[4] [5] [6] [7] [8] [9]} So let’s see what our colleagues in Wisconsin have to say about it, with their state-wide sewage monitoring.

First, consider the barplots of viral strain proportions over time, as shown here. (Click to embiggen, or use the references below, or this link, to consult the original.)

• The horizontal axis is time, biweekly for about 3.5 years.
• The vertical axis is the proportion of sequences seen for each viral variant.
• Each column of colored bars is a stacked bar chart, showing you the proportion of sequences seen in sewage for a given variant, over that 2-week period.
• The color legend is on the right, but here it only shows the top variants for the most recent period. Of course you can go to the reference below for all the details.

Now, note a few things carefully about the right most bar for 2025-Aug-11, the latest data:

• Everything of consequence in an Omicron substrain now. The rest of the variants are practically extinct. That is, the virus has so optimized itself for infecting us, that it’s down to just 1 specialist variant, Omicron. But there are lots of subvariants!
• The dominant subvariant right now is XFG (purple). NB: In the variant naming convention, names beginning with “X” are recombinant, i.e., fusions of more than 1 other variant.
• The variants recommended by the FDA are LP.8.1 and its superclass JN.1.
  • LP.8.1 is the green one, number 3 in the color legend. It’s very tiny, near the bottom of the bar.
  • JN.1 is the orange one, in 12th place in the color legend. It’s way down at the bottom.

Initially, this looks pretty discouraging: we’re about to get jabs (you are, aren’t you?) with a booster for a strain that’s completely a minority player, not the big bad XFG.

But… look a bit back in time (bars further to the left). I know it’s hard to read here, but it’s clearer in the interactive version on the Wisconsin web site: the 7th bar from the right corresponds to 2025-May-19. The long green bars there mean that the LP.8.1 strain was dominant then, so the decision to pick that strain was reasonable then.

But really, the question we’d like answered is whether the vaccine strains JN.1/LP.8.1 are still (somehow!) a reasonable choice now, when all the action is from XFG?

For that, we consult the phylogenetic tree of SARS-CoV2 viral variants (constructed from NextStrain clades and PANGO lineage information). If you don’t know what that is, think of it as an evolutionary family tree of the virus. Two strains that are very close in the tree (number of links to travel between them) are actually very close in their genetics, and a vaccine for one will likely give coverage for the other. (“Likely”: sequence similarity isn’t everything, e.g., if there’s a single black magic mutation dramatially increasing infectiousness. But all else being equal, sequence similarity is a good measure.)

Here’s the tree constructed by our friends in Wisconsin (click to embiggen, or use this link or the references to consult the original).

Have a look at the upper right:

• Go to the upper right corner, then back off to the left 4 levels. You should be looking at a node labeled 24A (JN.1). That’s the root strain recommended for vaccines this fall.
• An immediate descendant of that, to the right one level and just a skosh down, is 25A (LP.8.1). That’s the recommended target for vaccines this fall.
• Directly below 25A (LP.8.1) is 25C (XFG). That’s the dominant strain right now!

So the dominant strain right now is a direct descendant of the JN.1 lineage, and an immediate sibling of the LP.8.1 lineage. A vaccine for either of those should still provide excellent coverage against XFG, all else being equal (no “evil miracle” mutations).

Conclusion: Get this booster. Yes, our institutions are sclerotic, have always been too slow, and are now wildly corrupted with malign actors. However, the surviving FDA & CDC scientists last May got the VRBPAC committee to recommend something which should serve us well.

So that’s the vaccine that’s here to deal with. Its efficacy looks like a pretty good shot on target for this winter. But what about its safety?

COVID-19 vaccines, especially the mRNA vaccines from Pfizer & Moderna, have been proven safe and effective beyond a reasonable doubt. Still, people are just twitchy about them. Given the amount of disinformation, ignorance and willful lying for political purposes that we live in now, I guess this is understandable.

So once again on this CLBTNR, we’ll take a look at the data. Today we go through 3 takes on the safety of the vaccines: 2 very good, and 1… less so.

Take 1: All of Denmark, 1 Month After Vaccination

Recall that our upcoming boosters are for LP.8.1, a direct descendant of JN.1. That means safety data about a JN.1 vaccine is quite relevant now.

Fortunately, Andersson and colleagues have published just such a safety study ^[10] using essentially all the available electronic medical records in Denmark. (This is one of the benefits of universal health care: the universal medical records enable huge datasets that can explore hypotheses in much more scientific detail!)

First, let’s have a look at their study cohort, shown here (click to embiggen):

• Note the size: 1.5 million subjects, 1 million vaccinated and 0.5 million unvaccinated.
  • That’s not the entire population of Denmark (around 6 million in a 2025-Jul-01 estimate), but it’s probably everybody who had any contact with the medical system in the study period 2024-2025.
  • This is a very big study, essential impossible to replicate in the US with its fragmented, expensive health care with multiple incompatible electronic medical records systems and sometimes vicious insurance gate-keeping to avoid medical treatment.
• Since they selected those aged ≥ 65 or with higher risks, the population skews a bit older. We should expect to see more “old people problems” than in a general population.
  • Indeed, the most frequent co-morbidity was “chronic cardiac disorder”.
  • It also skews a bit female, which is to be expected given male/female life expectancy differences.
• It looks like, in the vaccinated population, there were about 86% included because of age, and 13% included because of risks. So it’s mostly a study of Danish seniors.

The paper’s a little unclear to me on this subject, but what it appears they did was ignore the unvaccinated population, and compare 29 different risks in the vaccinated population. The comparison was 28 days after vaccination vs the rest of the study period. So they’re looking for fairly prompt, acute reactions to the vaccine in the month immediately following.

They then computed, for each type of event, an incident risk ratio. It basically amounts to computing the ratio of the risk rate per day in the time 28 days after the vaccination. A ratio < 1 indicates less risk in the post-vaccination month; a ratio > 1 indicates more. A ratio near 1, especially with a 95% confidence interval straddling 1, means there’s no significant difference.

There are multiple ways to compute the confidence interval here:

• The Clopper-Pearson method for binomial proportion confidence intervals,
• Our own unpublished and mostly untested, but theoretically pleasing, method of Gauss hypergeometric functions for ratios of Beta-distributed variables, and
• Poisson regression.

They chose the last method, Poisson regression, to get them an event count and confidence intervals to fold into the ratio to get a ratio confidence interval.

I could check their work with either of the other 2 methods, but have not done so and will not unless (somehow?) there’s demand. A quick spot check, dividing the mean events per 100k person-years in both groups gives an estimate close to the mean value they’ve plotted. So it looks honest, at least from a reasonable distance.

Have a look at the forest plot on the right of this figure.

• Each row is one of the 29 events they checked for, based on observation of what happened before in vaccinated populations, and what happens to older populations in general. There’s no insinuation that vaccines cause any of this, just that these things happen, particularly to older people, so they checked the incidence rates.
• In most cases, the mean of the ratio is < 1, meaning the risk is lower immediately following vaccination.
• However, take a closer look at the error bars.
  • In almost every case, the error bar spans a ratios < 1 to ratios > 1. That means in those cases there is no statistically significant evidence to point to any difference in the event rates immediately after vaccination vs otherwise.
  • In only a few cases, the ratio is < 1 and the 95% confidence interval is also bounded below 1. This means there is evidence that you’re safer from that risk in the month following vaccination… though judging by the ratio, not by much.

Conclusion: For the 29 risk factors relevant to this cohort, there’s no evidence that risks immediately following vaccination are any different from other times. Vaccines do not increase any risks immediately following their administration.

A Mathematical Digression: Poisson Regression & Adjusted Incidence Rate Ratios

It occurred to me that for most people it’s not obvious why Poisson regression is a useful tool for calculating adjusted Incidence Rate Ratios (IRRs). So let’s fix that! (The Wikipedia page on Poisson regression is a good starting point.)

Poisson regression tries to predict a count of events $Y$ (e.g., number of medical adverse events) from a vector of features $\mathbf{x}$ (e.g., age, vaccination status, risk status). Predicting the log mean of $Y$ conditional on $\mathbf{x}$ with regression coefficients $\alpha$ and $\beta$:

This would fit your observed values of $Y$, but adjust them a bit so they make sense as groups with the covariates $\mathbf{x}$.

Now if you want to compare 2 groups, with observed counts $Y_1$ and $Y_2$ with group covariates $\mathbf{x}_1$ and $\mathbf{x}_2$ (say, vaccinated and unvaccinated people within the same age cohort), then you’d use the regression model like this:

Take the difference, and you get a log estimator (almost) for the ratio:

So this plus the uncertainty estimates on $\beta$ from the regression get you an estimator on the ratio and 95% confidence limits.

A couple caveats:

• Yes, this depends on the coding levels for $\mathbf{x}$. But if you have 2 groups, say vaccinated and unvaccinated, coded as 0 and 1, then $\mathbf{x}_1 - \mathbf{x}_2 = 1$, conveniently enough.
• Yes, the ratio of the expectation values is not the expectation of the ratio. Ratio statistics is a whole ‘nother thing. See, for example, our method on a method of Gauss hypergeometric functions for ratios of Beta-distributed variables to get some idea how hairy that gets. The Poisson method used here is apparently good enough, often enough, that it’s widely used.
• The variables being predicted are not actually counts, but rates. That is, there’s some kind of normalization done for each covariate group, e.g., divide by the number of fully vaccinated 18-44 year olds to get an incidence rate, say, per 100k person-years. That mildly complicates things, but is intellectually straightforward.

In the end you get (almost) an estimator for the incidence rate ratio, adjusted for the covariates, and a 95% confidence interval on it.

(I’d have done it differently using my method of ratio statistics on Beta-distributed event probabilities, but I admit that’s a niche taste.)

Take 2: All of Norway, 3 Years After Vaccination

So that’s the boring, safe story for no risk increase in the short term.

What about longer term?

We definitely see increased all-cause mortality rates at the onset of the pandemic. Were these due to the vaccines, or due to COVID-19 itself (and its disruption of health care in general)?

For that, we turn to a 3-year study by Dahl, et al. ^[11], who looked at all-cause mortality in a similarly broad population in Norway (universal health care!), over 2021-2023.

Note that this is a preprint, which is not as yet peer-reviewed. So… grain of salt.

First, let’s look at their study cohort, the summary table of which is shown here.

• It was a retrospective cohort study, including just about everybody over age 18 living in Norway in the years 2021-2023.
  • They were able to mine real-time national health registry data to obtain a study cohort of 4,645,910 people.
  • The 2024 population of Norway is around 5.5 million, so this was nearly the entire country in 2021-2023.
  • Subjects were categorized as unvaccinated, partially vaccinated (1 or 2 doses), and fully vaccinated (3+ doses).
    • People changed vaccination groups upon receiving a new dose. This was reported in real time by the national electronic medical records system.
    • These are obviously not the JN.1/LP.8.1 vaccines of this year, but rather the mRNA vaccines first available in 2021 and their modified versions through 2023.
    • If you want to study long-term effects, you have to look long term, which means including older treatments like the very first mRNA vaccines. Yes, mRNA vaccines have been in use for long enough that we can look at the first versions as having been “in the old days” of 2021!
• Death outcomes were from the National Population Register.

Now let’s consider their calculations. They stratified by analyzing each age group separately. Within each age group, they performed Poisson regressions to adjust for covariates like gender, place of residence, and by whether they were in a high-risk group.

These Poisson regressions yielded an adjusted incidence rate ratio of all-cause mortality, for each vaccination group compared to the unvaccinated. This looks almost exactly like the method of the previous paper, except that instead of measuring 29 adverse events for a few months, they measured only all-causes mortality for 3 years.

The results are shown here, in a forest plot.

• There are 4 groups, each in a horizontal strip. The most important one is the top strip, which represents all 3 years combined.
• Within each such group, they first stratify by vaccination status (unvaccinated, partial, and full) and then by age group (18-44, 45-64, and 65+).
• NB: Since the unvaccinated group is the baseline for comparison, the ratio for them is always exactly 1. We’re interested in whether the vaccinated groups show a ratio less than 1 (fewer deaths) or greater than 1 (more deaths).

Note that the adjusted IRR is always less than 1, and is in fact bounded below 1 by its 95% confidence interval! Also note that in the 3-year combined dataset, the 95% confidence intervals are very tight: a consequence of having 4.6 million test subjects! Universal health care is good for health care, but it’s also great for research.

(You might be curious about the one weird apparent exception for fully vaccinated, age 18-44, in 2021 only: the 95% confidence interval crosses 1. If you look at the number of deaths in that vax group and age group for that year, there were only 13! Basically this group was so well protected from dying that there were too few deaths to estimate accurately the 95% confidence interval! That was a very safe time to be a fully vaccinated young Norwegian.)

Conclusion: The vaccinated population had a lower death rate from all causes.

Take 3: Some of Florida, For 1 Year Early in the Pandemic

Levi, et al. report a different result (for a slightly different question) using data from Florida in the US. ^[12]

Note that this is also a preprint, which is not as yet peer-reviewed. So… grain of salt.

I’m not quite sure what to day about this one! It appears to be an attempt to use Florida data on Pfizer vs Moderna vaccination and match with vital statistics, to see if there’s an increase in all-cause mortality with one vaccine compared to the other vaccine.

The data, in outline:

• Matched cohort of 1,962,822 adults.
• Participants got a first dose of Pfizer or Moderna between 2020-Dec-18 and 2021-Aug-31.
• Outcomes sought were all-cause mortality, COVID-19 mortality, and cardiovascular.
• They claim a very peculiar result, that there was increased mortality with Pfizer compared to Moderna, as shown by the KM curves here.

As for their statistical methods: in 56 pages, there is not a single equation. There are big walls of descriptive word salad, and I understand some people like that. But it’s hard to say exactly what they did, without diving deeper than I care to do.

• There are a number of Kaplan-Meier survival curves, stratified by vaccine, for various populations. But…
  • There’s no mention of, say, a logrank $p$-value to assess whether the curves are statistically significantly different.
  • There’s no mention of a Cox regression that would normally be done here, to account for censorship.
    • There is some mention of logistic regression (death or not) on various predictors, much like the Poisson regressions used above to get adjusted incidence rate ratios.
    • There is no discussion of why logistic regression vs Poisson regression vs Cox regression, or the like. I mean, I love logistic regression, but from what I understand of the word salad it may not be the correct tool here.
• The data made me pretty uneasy:
  • Florida isn’t exactly famous for having reliable data like this. And the famous conservative slogan about dying “with COVID-19” vs “of COVID-19” means they’re depending on a judgment made by unknown persons with unknown agendas.
  • They exclude cases of suicide and murder, treating them separately as “negative controls”. I don’t like this: “all-cause mortality” should mean all causes. Suicidal depression or murderously poor impulse control & aggression seem like things worthy of inclusion.
  • Unlike the Norway & Denmark studies above, where vaccination as near-universal, in the US and in Florida in particular this was more of an iffy decision, depending on the person’s exposure to misinformation.
  • By choosing vaccination dates of 2020-Dec-18 and 2021-Aug-31, they’re looking only at people who were vaccinated very early in the pandemic. That population skews older and with more co-morbidities; we vaccinated them earlier because they needed the protection. (We denizens of Château Weekend are among them. Ok, not the cats, but the rest of us.)

I did like the fact that they started out with about 12 million records, and pared it down to about 950k in each arm, after careful matching of cohort properties. That part looks to be well done, but again there are no statistical details or equations for the cohort matching.

But why hasn’t anybody else seen this, and made a very, very loud noise about it? If their conclusion is true, why did the Norwegian data above show long-term protective effects against all-cause mortality? And why did the Danish data above show protective effects against 29 separate adverse events in the short term? Why has no pharmacovigilance study shown Pfizer inferior to Moderna?

If I were a referee, I’d stop the paper here and demand (a) explanations of why the dataset is not biased, (b) a clearer explanation of their statistical methods (including $p$-values attached to the KM curves), and (c) a meta-analysis including someone else’s data, showing that the effect is real.

But honestly, the thing that really made me twitchy was that one of the authors is Joseph Ladapo, currently surgeon general of Florida. Absent some really compelling argument to the contrary, he just looks problematic to me. The senior health reporter at the popular science venue Ars Technica has been writing negatively about him for years:

• As we worried previously, on this CLBTNR, this is the guy who (a) wants to ban all mandatory school vaccinations, and (b) compared vaccine mandates to slavery ^[13]:

  Every last one of them is wrong and drips with disdain and slavery.

• Back in 2022, he did a “dubious analysis” of Florida data and ended up recommending against mRNA vaccines for men ages 18-39. ^[14] The study was posted on the Florida Dept of Health web site, but without their logo, and without any authors. The critical review was not kind:

  Experts roundly dubbed the analysis “utter rubbish,” “extremely misleading,” and “comically bad.” Some called the analysis method “terrible,” and one epidemiologist called it “the absolute most batshit study design & analysis plan I have ever seen.” Others noted that the conclusion “smells of p-hacking” and data cherry-picking.

• Shortly after that in 2023, he was accused of fraud. ^[15]

  Florida’s health department opened and then closed an investigation into the state’s polarizing surgeon general, Joseph Ladapo, after a tipster claiming to have insider knowledge alleged that Ladapo “manipulated data” and committed “scientific fraud” in his final edits to what became a contentious, widely panned analysis on COVID-19 vaccine safety in young men.

  The investigation was closed, since the tipster did not want to be publicly exposed. However, there is evidence that the study authors – whoever they may be – deliberately avoided emailing about the project, passing notes to each other instead. This kept them off the official government records.

  Attempting to conceal your work is never a good sign in science.

• Later in 2023, as he continued to allege “crimes” in the vaccines, against masking, and promoting nonsense treatment like ivermectin, he tried to get the FDA and CDC on his side. ^[16]

  (Recall this was 2023, when the FDA and CDC were still science-run organizations.)

  Their response was blistering:

  In a four-page letter dated March 10, FDA Commissioner Robert Califf and CDC Director Rochelle Walensky easily debunk his inaccuracies, falsehoods, and bluster, while taking the opportunity to point out that he is failing the people of Florida in his role as a public health official.
  …
  In a knock to Ladapo’s dubious analysis on cardiac deaths, Walensky and Califf cited several studies that collectively indicate that “not only is there no evidence of increased risk of death following mRNA vaccines, but available data have shown quite the opposite: that being up to date on vaccinations saves lives compared to individuals who did not get vaccinated.” They also specifically highlighted a study looking at cardiac events, noting that “the risk of stroke and heart attack was actually lower in people who had been vaccinated, not higher” (emphasis theirs).

It’s a paper with a startling conclusion, but which just presents too many problems to believe it right out of the gate.

The Weekend Conclusion

1. The fall 2025 vaccine, optimized for LP.8.1, is very likely to be effective against the dominant variant, XFG. XFG is a recombinant (hence name starting with X) sibling of LP.8.1.
2. There is no acute short-term risk in the month after vaccination, compared to the rest of the time.
3. There is no increased mortality from vaccination, in fact dramatically the opposite as shown by the Norway data. (Levi, et al. will disagree about Pfizer vs Moderna, but I am extremely uneasy with their data and with one of the co-authors.)

Bottom line: Get the COVID-19 booster this fall, and get a flu shot while you’re there.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: Weekend Editor, “Why Writing About Vaccines is Hard for Me Now”, Some Weekend Reading blog, 2025-Jul-16. ↩

2: FDA Staff, “COVID-19 Vaccines (2025-2026 Formula) for Use in the United States Beginning in Fall 2025”, US Food & Drug Administration web site, downloaded 2025-Sep-10. ↩

3: Wisconsin State Labaratory of Hygiene Staff, “SARS-CoV-2 Wastewater Genomic Dashboard”, Wisconsin State Labaratory of Hygiene web site, downloaded 2025-Sep-10. ↩

4: Weekend Editor, “Coronavirus & Elections: The Winter of Our Discontent”, Some Weekend Reading blog, 2020-Nov-02. ↩

5: Weekend Editor, “Wastewater coronavirus RNA vs medical loads”, Some Weekend Reading blog, 2020-Nov-04. ↩

6: Weekend Editor, “Wastewater Revisited: Metagenomic Viral RNA and Medical Loads”, Some Weekend Reading blog, 2021-May-21. ↩

7: Weekend Editor, “Boston Wastewater Re-Re-Visited: Sewage Viral RNA vs COVID-19 Cases and Deaths”, Some Weekend Reading blog, 2022-Feb-04. ↩

8: Weekend Editor, “Why Writing About Vaccines is Hard for Me NowSARS-CoV2 Cryptic Sequences in NYC Wastewater: Why Not to Sleep Well at Night”, Some Weekend Reading blog, 2022-Feb-07. ↩

9: Weekend Editor, “COVID-19 mRNA in Boston Wastewater”, Some Weekend Reading blog, 2023-Jul-06. ↩

10: NW Andersson, et al., “Safety of JN.1-Updated mRNA COVID-19 Vaccines”, JAMA Network Open, 8:7, 2025-Jul-28. DOI: 10.1001/jamanetworkopen.2025.23557. ↩

11: J Dahl, et al., “COVID-19 mRNA-vaccination and all-cause mortality in the adult population in Norway during 2021-2023: a population-based cohort study”, medRχiv, 2024-Dec-16. DOI: 10.1101/2024.12.15.24319058.

NB: This is an as yet not peer-reviewed preprint. ↩

12: R Levi, et al., “Twelve-Month All-Cause Mortality after Initial COVID-19 Vaccination with Pfizer-BioNTech or mRNA-1273 among Adults Living in Florida”, medRχiv, 2025-Jul-22. DOI: 10.1101/2025.04.25.25326460.

NB: This is an as yet not peer-reviewed preprint. ↩

13: B Mole, “In win for infectious diseases, Florida to end all school vaccine requirements”, Ars Technica, 2025-Sep-03. ↩

14: B Mole, “That Florida ‘analysis’ on COVID vaccines is—you guessed it—total garbage”, Ars Technica, 2022-Oct-11. ↩

15: B Mole, “Florida surgeon general fudged data for dubious COVID analysis, tipster says”, Ars Technica, 2023-Feb-23. ↩

16: B Mole, “Florida surgeon general wrong on vaccines and bad at his job, CDC and FDA say”, Ars Technica, 2023-Mar-13. ↩

3 Monkeys

When I grew up in the US, there was a saying labeled moral instruction but really a joke, about 3 monkeys. One covered his eyes (“see no evil”), one covered his ears (“hear no evil”), and one covered his mouth (“speak no evil”). I was surprised to learn recently that they are actually of 17th century Japanese origin.

While I applaud the general theme of “don’t get involved with evil”, the usual misinterpretation here is that if you don’t see it, then it didn’t happen. So it sort of encourages a withdrawal from being morally engaged with the world, and simply hiding evil or hiding from it. (The origin in Japan is, of course, much more nuanced. I’m speaking here of the naïve interpretation of my childhood.)

Alas, this seems to be diagnostic of a moral failure of much of American life: if something can be concealed, then taking responsibility can be avoided.

This was brought to mind by an encounter with the following 3 monkeys.

Monkey 1: Police Turning Off Supervision on AI

It’s no secret that here on this Crummy Little Blog That Nobody Reads (CLBTNR), we are most emphatically not fans of LLM artificial intelligences. They do not answer questions; they supply convincing replies structured around “what would a plausible continuation of this conversation look like, irrespective of truth”.

Nonetheless, people are easily duped into trusting them, since they sound convincing. Now, it seems, even police are using AI to generate case reports! ^[1] DraftOne is a report-writing tool that will do things like summarize body-cam videos, with dubious integrity. It’s terrifying that such reports then go into records and into court.

The software initially has a few not-very-effective safeguards:

• Putting a bit of nonsense characters into the report, forcing the submitting officer to edit them out, and in the process read the report.
• Requiring a certain number of manual edits before the report can be submitted, again to encourage reading and checking the output, something which humans deeply resist doing.
• Labeling the parts of the report that were AI-written, so lawyers can see if they need challenge later.

Police departments testing the software have done the most bone-headed thing possible: turning off all the safeguards!

This is serious. Not only because of the inevitable hallucinations, but because of the well-known bias of AI visual processing programs against non-whites and women. If you’re in court, do you know the report is the officer’s memory, or a fable fabricated upon viewing his body-cam video?

Sigh: In the 3-monkeys morality, if you don’t know then nothing bad happened.

Monkey 2: Meta Hides Evidence of Child Sexual Predators

Meta, the parent company of Facebook, sometimes does research on how people react to their products, in particular the Metaverse. Then their lawyers got involved, gagging the researchers. ^[2]

It seems that researchers found (a) young children using the Metaverse a lot, and (b) they were often sexually propositioned. Meta lawyers immediately (and correctly) recognized this as a liability exposure for the company. But instead of telling the company to make sure not to do bad things, they told the researchers to suppress evidence of bad things.

Sigh, 3-monkeys morality again: if you forbid finding out what happens to children, then you have no responsibility for what happens to children.

Monkey 3: Donald Trump Lying in Court About Epstein

As anyone even vaguely alive and paying attention knows, there’s a big flare-up of interest in Trump’s relationship with Jeffrey Epstein, Ghislaine Maxwell, and the sexual procurement of children for those men.

For a long time, Trump has been attempting to distract attention and deny the existence of any such evidence, while refusing to let the Department of Justice release the files. Now the Wall Street Journal has a small fraction of the goods, obtained from the Epstein estate. ^[3]

It famously includes a mildly bawdy ‘birthday letter’, with a silhouette of a woman’s body and Donald Trump’s signature placed to resemble pubic hair.

The really interesting part is that Trump has repeatedly denied the existence of such a letter, including denials in court by his attorneys. Even now, he is resorting to his trademark defense of calling it ‘fake news’, although handwriting experts say the signature matches and the chain of custody of evidence from the Epstein estate is solid.

Sigh, poor little 3rd monkey: even if you deny the existence of your evil deeds, you still performed evil deeds.

The Weekend Conclusion

While the 3 monkeys are an instructive fable telling us not to be involved in evil, they are not telling us that if we don’t perceive evil then it’s not our problem! It is not a moral response to the world if we are destroying evidence and obstructing justice in preference to doing good things and not doing bad things in the first place!

A true moral response to the world involves a constant evaluation of whether what we see is right, and our degree of responsibility in making it that way. Most of all we need to look inside ourselves, encouraging the good and discouraging the bad. All this requires honest perception of good and evil, within and without, not just being blind and deaf to responsibility.

As Rabbi Heschel said,

“Above all, the prophets remind us of the moral state of a people: Few are guilty, but all are responsible. If we admit that the individual is in some measure conditioned or affected by the spirit of society, an individual’s crime discloses society’s corruption. In a community not indifferent to suffering, uncompromisingly impatient with cruelty and falsehood, continually concerned for God and every [person], crime would be infrequent rather than common.”

— Rabbi Abraham Joshua Heschel, The Prophets.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: T Parmar, “Government Documents Show Police Disabling AI Oversight Tools”, Mother Jones, 2025-Aug-15. ↩

2: J Swaine & N Nix, “Meta suppressed research on child safety, employees say”, Washington Post, 2025-Sep-08. ↩

3: K Safdar & J Palazzolo, “Epstein Birthday Letter With Trump’s Signature Revealed”, Wall Street Journal, 2025-Sep-08. Unpaywalled archive.is link.. ↩

It’s All Summed Up in 4 Words

On 1935-Jul-17, the Hollywood-focused newspaper Variety wrote one of its most famous headlines, traditionally repetitive rhyming slang words rendering the meaning almost inscrutable. In saying that rural filmgoers of the day had no interest in films about rural life, they memorably wrote ^[1]:

Sticks Nix Hick Pix

Meaning: people who live in rural areas (“the sticks”) say no to (“nix”) rural-focused movies (“hick pix”). It manages to be completely insulting, both to rural people as well as reflexively to the Variety headline editors themselves (“we’re so dumb we actually said this, in writing”).

A couple days ago, Maureen Dowd writing at The New York Times has achieved a similar degree of perspicuity, summing up the pig-headed ignorance of RFKJr around vaccines in just 4 words ^[2]:

Vax Quack Lacks Facts

(Be sure to click through to see the archival picture of a polio victim in an iron lung. It’s hard to convey to people today how terrifying polio was to my elders when I was a kid in the 50s and 60s. As a little kid, I only understood that if I got the polio vaccine, then it would be possible to go to the beach in August, which was the best beach month. Since then, I’ve grown to realize what a monster we dodged with the polio vaccines.)

This is personal for Dowd, since she almost died of rubella when she was 3 years old. It’s a bit personal for me as well, since I also had rubella at the beginning of first grade (though in that time and place it was called “German measles”). It meant that when I went back to school, everybody else understood “how school works”, and I did not.

And last spring, here at Château Weekend, we got MMR boosters (measles/mumps/rubella) along with COVID-19 boosters. ^[3] That was because the anti-vax knuckleheads have loosed again the most contagious disease known to humanity, measles, which has no treatment but is easily preventable. (Given the high $R_0$ for measles, you need about 95% of the population to be vaccinated to prevent outbreaks. It really is just that bad a disease, and we don’t have to get it!)

Dowd points out that we are bringing needless dangers down upon our children’s heads:

Between school shooters and R.F.K. Jr., children in America are vulnerable in ways they don’t have to be. Officials are endangering children instead of shielding them.

• Kennedy has impounded $500 million in grants for mRNA vaccine research and manufacturing of mRNA vaccines.
• Then Kennedy impounded a $600 million grant for vaccines for bird flu, which looks to be quite deadly if it ever hops to human hosts.
• In a measles outbreak in Texas, Kennedy promoted vitamin A and cod liver oil on Fox news; subsequently, several unvaccinated children were hospitalized for liver damage from overdosing on those.
• In 2019, Kennedy claimed to Samoans that the MMR vaccine caused the deaths of infants. The subsequent measles outbreak killed 83 Samoans and 500 Tongans.
• Before testifying before Congress last week, he did not bother to be briefed by CDC experts, especially on COVID-19 and measles. He got his ideas from other cranks, instead.

Yes, he lacks facts.

No, he does not lack for blood on his hands. (Children’s blood, in case that matters to you.)

It’s Not Just RFKJr

Of course, it’s not just RFKJr. He’s got a whole posse of anti-vax weirdos in local positions of power. Whether he inspires them & sets them loose or whether they are just as a group committed to death is not particularly important.

Case in point: the Florida surgeon general Joseph Ladapo has announced his intent to end all school vaccination requirements. ^[4] This includes even the obviously important ones like Hib, pertussis, diphtheria, measles, tetanus, RSV, and even polio.

He thinks, and I am using the verb ‘think’ here very loosely, that vaccine mandates are like slavery:

Every last one of them is wrong and drips with disdain and slavery.

Defining down slavery is an… interesting position for a Black man in the US to take!

He’s got a long history of being anti-vaccine and spreading misinformation. He was previously smacked down by the FDA and CDC, before Republicans neutered them. For example, he pushed the de-worming drug ivermectin against COVID-19. He’s also been credibly accused of altering data, to make analyses show mRNA vaccines for COVID-19 did various bad things.

And yet… this is what Republicans want: ignorant policies, dishonestly presented, which will only cause deaths. One wonders if the political virtue signaling will be worth it to them.

The Weekend Conclusion

Honestly, we’re in such a bad place I barely even know how to describe it. The correct solution, of course, is a change of government and very many criminal trials and convictions of the band of grifters in power.

In the meantime… “Vax Quack Lacks Facts” is a regrettably accurate summary.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: G McCall, “Sticks Nix Hick Pix”, Variety 119:5, 1935-Jul-17.

The corresponding Wikipedia page is informative. ↩

2: M Dowd, “Vax Quack Lacks Facts”, New York Times 2025-Aug-30.

NB: Link goes to an archival site, because the original is regrettably paywalled. ↩

3: Weekend Editor, “Getting Vaccinated Because… Knuckleheads!”, Some Weekend Reading blog, 2025-Mar-17. ↩

4: B Mole, “In win for infectious diseases, Florida to end all school vaccine requirements”, Ars Technica, 2025-Sep-03. ↩

Cryptography and the Venerable TM-82

So, cryptography. (No, not “crypto” as in Bitcoin, but good ol’ respectable cryptography, as in sending private messages back and forth.)

Cryptography changed drastically in the late 70s, with the invention of public-key, trap-door ciphers:

• It’s relatively easy to compute the encrypted form of a message from the cleartext, especially since you have the key.
• It’s relatively easy to compute the cleartext of a message from the cryptext, if you have the key.
• It’s insanely difficult to compute the cleartext of a message from the cryptext without the key.

So basically we hope that an encryption function is what’s called a trap-door function: it’s easy to fall through the trap-door (encrypt with key), it’s easy to come back if you know where the secret catch on the trap-door is (decrypt with key), but it’s very hard to come back through the trap-door if you don’t know where the catch is (decrypt without key).

It would be ideal if we could prove decryption was an $NP$-hard function, which is theoretical computer science for something that’s hard to compute, but easy to check the answer. We hope encryption and decryption with key are polynomial time, but decryption without key is at least exponential.

There are no such functions known. That is, we do not have a formal mathematical proof of anything. However, there are heuristic functions that look like this so far, i.e., nobody’s discovered a more efficient decryption step. (For that matter, we don’t even know for sure if $P = NP$ which would make all this collapse and set loose magic in the world. Most knowledgeable people bet that $P \neq NP$, but there are as yet no good proofs. Instant fame if you find one, which is why there are so many crank attempts every year.)

Prime factoring large (hundreds to low thousand decimal digits) integers is one such problem: it’s hard to find the prime factors, but it’s easy-ish to multiply them back to check.

In 1977, Rivest, Shamir & Adelman invented what is now known as the RSA system based on this. ^[1] The best factoring algorithms back then, and indeed now, require time exponential in the number of digits of the integer. (Their system provides some more interesting features, such as you can publicly disclose an encryption key to send messages to you, and you can cryptographically sign messages so the recipients are sure it’s from you. We’ll pass over those aspects for today.)

RSA showed how to exploit this to make an effectively unbreakable system, using modular exponentiation by repeated squaring. Over the years, we’ve had to make the keys longer and longer as the code-breakers get faster computers, but that’s the thing about an exponential complexity: just a little bit longer key means much harder to break.

The paper starts out with prophetic words:

The era of “electronic mail” may soon be upon us…

Soon, indeed! (Yes, I had an ARPANET email address even back then.)

Still, the US government’s reaction was as paranoid as you might expect: they attempted to declare it retroactively classified, then they declared it a “munition” to prevent its export (in an era when the net was getting started, anything was deemed exported), and even threatened the authors and MIT. ^[2]

Quantum Computers and Factoring

The RSA algorithm involves picking, in a certain way, a large integer $N$ which is the product of exactly 2 prime factors $p$ and $q$:

You then (approximately; I’m over-simplifying lots of details here, including conditions on $p$ & $q$, and secure signatures) disclose $N$ publicly so people can encrypt stuff to send to you, but keep $p$ and $q$ secret. They are your decryption keys.

The best factoring algorithms on the best conventional computers are helpless if $N$, $p$, and $q$ are large enough, like several hundred or a couple thousand digits.

People quickly began to suspect that doing polynomial-time factoring would require a quantum computer, which is a different order of beast from regular computers. Indeed, in 1994 Peter Shor published ^[3] an algorithm doing exactly that. (Wikipedia has an explanation if you don’t want to wade through the paper, but both are really only for fans of math.)

There were no immediate implementations, as there were no immediate quantum computers. But people started to get nervous. RSA is commonly used in encrypted business, diplomatic, and military communications, at least in the initial key exchange phase. There’s a lot riding on the confidentiality of those, so… nervous.

Now, the quantum computers of the day were (and still are, really) quite small and elementary. So you’d have to start small to demonstrate Shor’s algorithm. That’s what happened:

• In 2001, Vandersypen and colleagues ^[4] worked extremely hard to create a quantum computer having 7 qubits total, consisting each of a single spin-1/2 nucleus. Keeping those from thermalizing with the environment and decohering is hard! These nuclei were interrogated with nuclear magnetic resonance techniques, but the system as a whole wouldn’t scale to a larger number of qubits.

  Still, they managed to use a quantum computer and Shor’s algorithm to prove:

  \[15 = 3 \times 5\]

• There’s a lot of effort going on here behind the scenes. In order to reduce somewhat the resource consumption, Martín-López and colleagues in 2012 ^[5] figured out a way to reduce the number of required qubits. Instead of having an $n$-qubit register, they took a single qubit and recycled it $n$ times. The result, as one can see after some math, is about 1/3 the number of qubits required by the more conventional Shor protocol. (Conversely, one could perhaps factor numbers with 3x the digits using the same number of qubits?)

  This made their method more likely to be scalable to longer numbers.

  Still, given the constraints of their experimental setup, they were able to use a single qubit and – apparently straining mightily – came to the conclusion that:

  \[21 = 3 \times 7\]

There were maybe 4 or so other attempts around the same time, but I’ll spare you the details. More modern attempts at quantum computing might be doing better, but it’s still a bit murky to me. (Also, an attempt to factor 35 was made, but failed.)

But before you laugh too much (a little is ok), let me remind you that these are not engineering papers (“Hey, look at this useful thing we made!”). They are, instead, science papers (“Hey, look what’s true about mathematics, quantum mechanics, and nature!”). They demonstrated very impressively that:

• Shor’s algorithm actually works,
• Quantum computing is hard, and
• Scalability in particular is a pain in the rear.

So the RSA prime factors cipher may not be in immediate danger, but the principle has been demonstrated. Now it’s a matter of engineering.

And you know how engineers are.

(Especially when they can pull the rug out from under all the finance people using RSA for encrypted banking transactions. Who wouldn’t like to annoy the finance bros?)

Does It Help If You Use a Dog?

That brings us today’s paper.

Everything up to here is prolegomena, setting up the background for The Main Joke. Why bother going through all that just for a joke? As the eminent science writer Martin Gardner said, in his Annotated Alice: Definitive Edition ^[6], from the introduction to the original Annotated Alice:

But no joke is funny unless you see the point of it, and sometimes a point has to be explained.

So now that you know at least the bare bones about RSA ciphers, factorization algorithms, and the danger to them posed by quantum computers… you’re prepared to joke about them in the proper fashion!

Gutman & Neuhaus ^[7] have written a very silly paper to make a very serious point: most of the demonstrations of factoring with quantum computers have either been physics experiments not yet relevant to cryptography, or have been pretty much rigged to look more impressive than they really are.

The ‘Physics Experiments’

Some of the factorizations of ridiculously simple integers like the above are mostly about physics experiments of various sorts, say, maintaining quantum coherence in a system of nuclear spins. They demonstrate the feasibility of quantum computing by doing Shor’s algorithm on a trivial case.

As a physics experiment, this is fine and noble. As a claim about RSA crypto security, they are ridiculous. Most such claims were not made by the experimenters, but added by credulous media.

The ‘Stunt Factorizations’

Nevertheless, people can’t resist “stunt factorizations”, in which the problem has been carefully prepared to have hidden structure to exploit and factorize on trivial amounts of hardware. (Analogous, the authors say, to the “force decks” used in card tricks that look like a full deck of cards, but really contain only one or two.)

• For example, if $N = p \times q$ where $p$ and $q$ are prime, but differ only in a few bits, then $N$ can be factorized by integer square root and brute-force search.

  No real-world RSA system would allow such an $N$, but this inconvenient fact is seldom mentioned.

• Another example is the factorization of 1,099,551,473,989 which in binary begins with 100000000000000… thereby hinting that a game of some sort is afoot.

  Another such game might be jokingly termed Callas Normal Form, after Jon Callas who pointed it out. Here, if $n \le m$:

  \[\left\{ \begin{align*} p &= 2^{n} - 1 \\ q &= 2^{m} + 1 \end{align*} \right.\]

  then $N = p \times q$ begins in binary with $n$ 1 bits, then $m-n$ 0 bits, and ends in $n$ 1 bits. At that point, factorization proceeds more via hijinks than by cleverness.

  Again, this is a case no real-world RSA toolkit would generate.

There is a paper out this spring and published this summer from a Chinese group claiming to have used a D-wave quantum computer to solve RSA-2048: factorize 2048-bit $N$ values into pairs of primes $p$ and $q$. ^[8]

In words attributed to HL Mencken: “Interesting, if true.”

However, according to Gutmann & Neuhaus, all the examples in the paper are “sleight-of-hand” numbers. They were specially chosen so that $p$ and $q$ differ by either 2 or 6. So it’s perfectly reasonable to take the integer square root of $N$ and search nearby! In slightly more detail:

• There exists a 1024-bit integer $x$ halfway between $p$ and $q$.
• There exists an integer $d$ such that $p = x - d$ and $q = x + d$.
• The only choices allowed for $d$ are 1 and 3, depending on whether $|p-q|$ is 2 or 6, respectively.

So $N = pq = (x-d)(x+d) = x^2 - d^2$, so $N + d^2 = x^2$ must be a perfect square. If $d$ is either 1 or 3, just try $d = 3$ and see if it’s a perfect square:

• Let $x$ be the integer square root of $N + 9$ and $r$ be its remainder.
• If $r = 0$, then $d = 3$, so the factors are $x-3$ and $x+3$.
• Else if $r = 8$, then $d = 1$, so the factors are $x-1$ and $x+1$.
• Else the problem is not one that has been rigged for you in advance (or at least not in this fasion).

These tricks are common. As the authors say:

So far as we have been able to determine, no quantum factorisation has ever factorised a value that wasn’t either a carefully-constructed sleight-of-hand number or for which most of the work wasn’t done beforehand with a computer in order to transform the problem into a different one that could then be readily solved by a physics experiment [23] [10].

The VIC-20 8-bit CPU

Just to rub in the point, the authors show this can be done on a consumer-class computer from 1980: the Commodore VIC-20.

This used a 6502 processor (introduced in 1975, which I first encountered in about 1976 or 1977), with:

• 3 registers of 8 bits each,
• a data bus 8 bits wide, and
• a 16 bit address space.

Typically configured the VIC-20 had 20kb of ROM and a mere 5kb of RAM. But only 3.5kb of the RAM was available to users, the rest being taken up with system stuff. The clock speed was a glacial 1MHz. (I remember when the Zilog Z-80 came out, at a blistering 5MHz. That’s a mere factor of 1,000 slower clock speed than computers of today. Given pipelining and other architectural parallelism tricks, modern hardware is much faster even than that.)

The small cases of $15 = 3 \times 5$ and $21 = 3 \times 7$ were done with lookup tables. The integer square root with remainder algorithm descends from one written by no less a luminary than John von Neumann himself, for the EDVAC vacuum tube computer in 1945.

They wrote some code in 6502 assembler, and ran it on an emulator. The paper points you to where to get the code, if you’re interested.

• The code was 427 lines long.
• The ROM image had 794 code and data bytes, 256 were for the number to be factored.
• The code required 1792 bytes of RAM, which fit easily.

Notably, no multiplication or division operations were required, which is good because the 6502 didn’t have that, much less for “bignum” integers with 2,048 bits!

Results: They replicated all 10 results from the D-Wave paper, each taking about 16.5 seconds if one took the number of clock ticks and divided by 1 MHz. Running it on a modern laptop took less than a second each.

Conclusion: The results reported in the D-Wave paper are trivial, since the examples were chosen via sleight-of-hand to be easily solved.

The D-Wave paper’s authors showed subtle comic taste in their choice to publish this joke, which I admire & applaud. However, they did not honestly admit to having done so, which I deplore: jokes are only funny if you let people in on the joke!

The Abacus

Given that the above-referenced integer square root algorithm was inspired by integer square roots on an abacus, you can probably guess what comes next.

They “implemented” the $15 = 3 \times 5$ and $21 = 3 \times 7$ factorizations on an abacus. Though, really, since this is done one digit at a time using the user’s memory as a buffer, there was nothing left for the abacus to do.

This is not (entirely) silly: it points up the triviality of implementation, meaning the physics experiments doing this were about physics, not cryptography.

The rest, though, is entirely silly.

They pointed out that to replicate the D-Wave paper’s factorization of a (sort of) RSA-2048 integer, they’d need 616 digits. Each column of an abacus is one digit, and they come typically in 9, 11, or 13 digit versions. Clearly some work on abacus hardware is required in order to continue the joke:

In fact the size of a 616-digit abacus is unpleasant to contemplate, so we leave the construction of such a bignum abacus to the reader, or perhaps an enthusiastic woodworking hobbyist with a YouTube channel.

Sounds about right to me.

The Dog

In order to further replicate the quantum factorizations of 15 and 21, they employed a ‘recently-calibrated reference dog, Scribble’, shown here.

This fine animal is apparently so well-behaved that in general he does not bark. However, upon vigorous play, he has been trained to bark 3 times:

Having him perform quantum factorization required having his owner play with him with a ball in order to encourage him to bark. It was a special performance just for this publication, because he understands the importance of evidence-based science.

Good dog!

He apparently failed at factoring 35, because he had learned to bark 3 times. That’s ok, the first quantum factoring attempt on 35 failed, too.

The RSA-2048 candidates proposed in the D-Wave paper were deemed beyond the scope of this dog.

No dogs were harmed in the course of this research:

According to most Codes of Ethics, Scribble’s contribution to this paper does not rise to the level where he is required to be listed as co-author. However since he was a participant in the work rather than the subject of an experiment his contributions are exempt from review board approval.

In fact, as far as reproducibility of this research, they correctly note one difficulty:

Finally, the apparatus for the canine-based factorization may be obtained from any animal shelter. Although our experiment used a Staffy, almost any dog breed should be suitable, although smaller yappy dogs may over-report values.

The Point

Almost all the reports of quantum factorization are either notable as physics experiments as yet irrelevant to cryptography, or as “stunt factorizations” using sham keys that no RSA cryptography system would permit.

The authors present several sensible criteria for factorization claims going forward. They’re about what you think:

• the factors should be chosen sensibly by the criteria used in cryptography (of which there are several),
• the experiment should be blinded (the factoring researchers are not permitted to know the number in advance, nor the solution until they find it), and
• the process should be repeated on 10 different values chosen independently from the experimenters, to show reproducibility.

The real question to me is: How do papers like the sham factorizations and the sleight of hand D-Wave paper get published? Shouldn’t at least one of the referees have some cryptography background to check for things like this? Shouldn’t there be a standard registry of appropriately chosen factoring problems, whose solutions are not revealed until someone solves them?

The thing about common sense is that it’s so uncommon!

Chicken

Sometimes, when reading a deliberately silly paper, one should calibrate it against The Standards.

One such standard is Doug Zongker’s famous “Chicken” paper & talk ^[9], from 2006-2007. Though published in the venerable Annals of Improbable Research, it was actually presented at a AAAS conference in 2007 (admittedly in the humor section, which is only fitting).

He mocks the form of a technical talk, without having the least bit of content. He shows many graphs, tables, and equations – all without meaning. He only says the word “chicken”, though with tone of voice to emphasize Very Important Points about chickens.

Be sure to stick around for the end of the video, when during the question period, someone asks a question using only the word chicken… and Zongker has a pre-prepared response slide just in case somebody did that. Now that’s preparedness surrealism!

The Weekend Conclusion

Dog factoring is not really a thing, of course, beyond satire. (Though it is good satire!)

But at Chez Weekend, we’re less dog-folk and more cat-folk. So far, attempts to get the 2 cats to factorize integers have been unsuccessful.

Still, there are a few members of family Canidae frequenting the Château Weekend grounds and gardens, shown here. It appears to be a wild fox, though a bit skinny. We’ve seen several of them running around the garden, playing cutely. They seem to have gotten control of the enormous rabbit population, and the otherwise adorable-but-ignorable chipmunks. The wild turkeys, several times fox-sized, are unlikely prey but still spooked. (Wild turkeys can fly, just… not very well.)

As you can see here, the Weekend Publisher (and the Assistant Weekend Publisher, not shown) disapproves of dogs of all sorts, August dies caniculares or not. (His opinions on factoring are as yet unknown.)

But all of us here are agreed: Ceterum censeo, Trump incarcerandam esse.

Notes & References

1: R Rivest, A Shamir, L Adleman, “A Method for Obtaining Digital Signatures and Public-Key Cryptosystems”, MIT Laboratory for Computer Science (now part of CSAIL), Technical Memo LCS/TM 82, April 1977. ↩

2: A couple weird stories:

• In the summer of 1977, the RSA algorithm was discussed in Scientific American, in Martin Gardner’s famous “Mathematical Games” column. I was an avid reader of that column in those days, and since I was entering MIT in fall 1977 as a physics grad student, I thought I’d pick up a copy of TM-82 for recreational reading.

  When I went to the publications office to ask for one, I got a deeply suspicious look, and questions like: “Are you an MIT affiliate?” And: “What are you going to do with it if I give it to you?” All very weird, but it turned out the Institute was fighting the US government in its effort to strangle the whole thing, and had temporarily stopped giving it out.

  I thought I looked like a scruffy grad student and not a spy, but whatever.

  But… they helpfully added that I could put my name on a waiting list to get it “when things clear up”. Being young & naïve, I did so.

  Eventually, I got the paper, after maybe 3-4 months.

  But in the meantime, some weird stuff happened, since I was apparently now on some very weird lists. I had a girlfriend in those days (yes, that’s weird too, given my lack of social skills, but it’s not the weird part of this story), whom I would call periodically long-distance (also a weird thing of those bygone days).

  Then one day her dormitory phone wouldn’t connect. She eventually got it repaired by her university, but the repair guy said there was a part missing. Apparently somebody had entered her room, taken the phone apart, decided it was too old to mess with, and put it back together incompetently.

  Was that a probable attempt at bugging her phone, related to my wanting a copy of an encryption paper? Sure feels like it!

  So maybe in some FBI/CIA/DSA database, there’s an entry about me from September 1977.

• On the subject of old phones: MIT had a system called “dorm-phone”, which was ancient. It didn’t really connect to the outside world, only to Institute phones. It was run through a relay rack in the basement of my graduate dorm. You could go down there and stand outside the door to the phone equipment room, hearing the relays go “clacketa-clacketa”.

  Years later, a colleague told me a weird phone story of when he first arrived at MIT.

  Seeing the ancient dorm-phone in his room, he correctly guessed that he could do hook-flash dialing: you rhythmically tap the hang-up buttons on the hook, with a short pause between digits. Like the 20mA current loop machinery in the dial, this feels to the phone switch like the rotary dial sliding over the contacts. So he made a quick call to a friend in the dorm, smiled at the oddity, and hung up.

  A moment later, his phone rang. The conversation went like this:

  Mysterious angry voice: Does your phone have a dial on it?!
  My colleague: Uh… yes?
  Mysterious angry voice: Then use it! (hangs up)

  Somebody had been in the relay room at the time, and heard the relays not going gently “clacketa-clacketa”, but “SLAM! SLAM!”. This sort of thing is hard on those ancient relays, so he worked back from the relays to the source number and expressed his fervent desire that this abuse should come to an end. (Possibly a Bad Word might have been used.)

  My colleague then realized that as a 70s-era phone hacker, he was far from unique in that environment. ↩

3: PW Shor, “Algorithms for quantum computation: discrete logarithms and factoring”, Proc 35th Symp Fndns of Comp Sci, 1994-Nov. DOI: 10.1109/SFCS.1994.365700. ↩

4: LMK Vandersypen, et al., “Experimental realization of Shor’s quantum factoring algorithm using nuclear magnetic resonance”, Nature 414:6866, 2001-Dec-20, pp. 883-887. DOI: 10.1038/414883a. PMID: 11780055.

There is an unpaywalled pre-print available at arXiv:quant-ph/0112176. ↩

5: E Martín-López, et al., “Experimental realization of Shor’s quantum factoring algorithm using qubit recycling”, Nature Photonics 6, 2012-Oct-12, pp. 773-776. DOI: 10.1038/nphoton.2012.259.

There is an unpaywalled pre-print available at arXiv:1111.4147. ↩

6: M Gardner, The Annotated Alice: The Definitive Edition, Penguin Books, 2001. ISBN-13: 978-0393048476.

The quote appears on page xiii of the introduction in my edition.↩

7: P Gutmann & S Neuhaus, “Replication of Quantum Factorisation Records with an 8-bit Home Computer, an Abacus, and a Dog”, Cryptology ePrint Archive, 2025/1237, version of 2025-Jul-19.

NB: The authors carefully explain one of their notational choices in footnote 1:

We use the UK form “factorise” here in place of the US variants “factorize” or “factor” in order to avoid the 40% tariff on the US term.

Just so you know what to expect, going in. (Fair enough, though? I like these guys. I mean, I really like them.) ↩

8: C Wang, et al., “A First Successful Factorization of RSA-2048 Integer by D-Wave Quantum Computer”, Tsinghua Science and Technology 30:3, p. 1270, 2025-Jun. DOI: 10.26599/TST.2024.9010028.

NB: As Gutmann & Neuhaus wryly note:

We note that the paper has, at the time of writing (March 2025) a publication date in the future (June 2025). It appears that the D-Wave device can also shift time and relative dimensions in space.

↩

9: D Zongker, “Chicken Chicken Chicken: Chicken Chicken”, Annals of Improbable Research 12:5, 2006-Sept/Oct.

NB: Originally published in the AIR in 2006, but later delivered at the Improbable Research session at the 2007 Annual Meeting of the American Association for the Advancement of Science (AAAS), in San Francisco, 2007-Feb-16. Video documentation is by Yoram Bauman.

The formal paper is here, replete with graphs, tables and equations. Deeply impressive satire. ↩

VERY Bad Doggies

Remember back in ancient times, like last April, when we wrote on this Crummy Little Blog That Nobody Reads (CLBTNR) about the DOGE boys being bad little doggies for apparently illegally exfiltrating NLRB data while turning off safeguards like logging & access controls?

Well, buckle up. It seems they’re now committing similar likely crimes at the Social Security Administration. This time, instead of just getting confidential info on NLRB court cases against Musk and cronies, they’ve gotten identity information on all Americans. ^{[1] [2]}

And by “all”, I mean living and dead, back to the dawn of Social Security.

The whistleblower here is no low-level stooge. It is, in fact, the Chief Data Officer of the Social Security Administration, Charles Borges.

• He reported internally to the (MAGA/DOGE) management of the SSA that the “Numident” (numerical identification system) database had been uploaded in its entirety to an unsecured cloud server by DOGE boys.
• This database contains names, Social Security numbers, places and dates of birth, citizenship, race, ethnicity, address and even parents names.
• This applies to anyone who has ever had a Social Security number, whether currently alive or dead.
• This seems to work out to about 450 million people who now have their identities completely exposed to identity fraud risk.
• It appears that the new senior MAGA/DOGE management of SSA actually approved this, even though it is widely believed to have been highly illegal, e.g., under the Federal Information Security Modernization Act (according to Borges).
• When internal appeals did not work, he made a formal whistleblower complaint to the Government Accountability Project. ^[3] That complaint was then forwarded to members of Congress and the US Office of Special Counsel.

From the complaint:

This vulnerable cloud environment is effectively a live copy of the entire country’s Social Security information from the Numerical Identification System (NUMIDENT) database, that apparently lacks any security oversight from SSA or tracking to determine who is accessing or has accessed the copy of this data. NUMIDENT contains all data submitted in an application for a United States Social Security card—including the name of the applicant, place and date of birth, citizenship, race and ethnicity, parents’ names and social security numbers, phone number, address, and other personal information. Should bad actors gain access to this cloud environment, Americans may be susceptible to widespread identity theft, may lose vital healthcare and food benefits, and the government may be responsible for re-issuing every American a new Social Security Number at great cost.

It’s bad enough that DOGE got access to the data, which they definitely should not have. But even worse that they just… took it and put it on a cloud server with no security and no logging to tell what they do with it.

In response, new SSA Commissioner Frank Bisignano denied that anything was insecure, that it was all “walled off from the internet”. We’ve previously written about who Frank Bisignano is, namely a Wall Street investment banker, formerly the highest-paid CEO in the US, who used layoffs as a constant threat against employees. He’s also a long-time Republican donor, in particular to Trump.

Do you really want to take his word on computer security issues?

I do not.

You can probably imagine what happened next: management retaliation. SSA people were instructed not to talk to Borges, which of course cripples his ability to do his job legally and ethically.

Journalist Marisa Kabas (and founder of The Handbasket) reported today that Borges has resigned, and supplies a copy of his letter of forced resignation:

As you can see, he says he’s forced out due to management retaliation making it impossible to perform his job “legally and ethically”. Management retaliation against whistleblowers of this sort is a federal crime, according to the Office of the Inspector General.

But it appears that lawlessness is no barrier to MAGA/DOGE, since it seems they immediately violated federal record-keeping laws by attempting to delete all record of this email from the inboxes of all who received it, according to Kabas:

I’m not a lawyer, but… it just looks like federal crime after federal crime committed by these guys: unlawful data exfiltration, whistleblower retaliation, destruction of federal records… Sometimes the coverup is worse than the original crime.

The Weekend Conclusion

I know dog training has progressed beyond the “swat ‘em on the nose with a rolled-up newspaper” doctrine of my youth. There are very few newspapers left, for one thing. But I kinda do wanna swat these ignorant fascists on the nose with a rolled-up newspaper. (Ok, maybe gently, ‘cause that’s who I am.)

I’d of course settle for a change of government, mass prosecutions, convictions, and imprisonments. That would be much better.

Say it along with me: Ceterum censeo, Trump incarcerandam esse.

Notes & References

1: A Revilla, “Whistleblower claims DOGE uploaded Social Security data to unsecure cloud server”, Engadget, 2025-Aug-26. ↩

2: J Brodkin, “DOGE accused of copying entire Social Security database to insecure cloud system”, Ars Technica, 2025-Aug-26. ↩

3: C Borges, “Protected Whistleblower Disclosure of Charles Borges Regarding Violation of Laws, Rules & Regulations, Abuse of Authority, Gross Mismanagement, and Substantial and Specific Threat to Public Health and Safety at the Social Security Administration”, Government Accountability Project web site, downloaded 2025-Aug 29, dated 2025-Aug-26. ↩

A Republican War on Weather Forecasting… Where Have I Heard That Before?!

I’ve been seeing all sorts of weird news items about Republicans getting conspiratorially stupid about weather forecasting. Now… where have we heard that before?

Oh, that’s right: it was right here on this Crummy Little Blog That Nobody Reads (CLBTNR), back on 2021-Jul-12. ^[1]

There were 2 particularly egregious cases, each surreal enough to earn a patch from Dissent Pins, as shown here:

• Representative Louis Gohmert (R-TX), often used as the reference standard for political stupidity, asked the US Forest Service whether they could change the orbit of the moon to fix climate change.

  And then he got mad when reporting about him talking to the Bureau of Land Management used the abbreviation BLM, because he feared people would think he was talking to/about Black Lives Matter. Because clearly that’s worse than thinking the US Forest Service can mount a space expedition to change the orbit of the moon.

• The second was our old friend, Representative Marjorie Taylor Greene (R-GA). She took a break from her usual allegations that:
  • Democrats are satanist cannibals running a child sex ring, or that
  • Muslims should not be allowed in public office, or that
  • Mass shootings are staged by liberals, or that
  • “Zionist supremacists” are causing Muslim migrations to drive whites to extinction, or that
  • Democratic officials should be executed.

  No, no: she had more important fish to fry. She claimed the California wildfires were deliberately started by PG&E in conjunction with the ever-present Rothschild family, using secret Jewish space laser stations, in order to clear a path for high-speed rail.

  (I almost wanted that one to be true, because I could at least apply for a gig on the secret Jewish laser space station. I bet the pastrami in the canteen would be really good.)

Hwæt! We in geardagum, þrym gefrunon Republicans

So what fell beasts do Republican heroes fight now, as did Beowulf of old? ^[2]

Apparently, the dark art of weather forecasting. No doubt there are witches involved, somewhere.

The billionaires want to shut down government weather forecasting so they can privatize it to make you pay them for it. The fossil fuel oligarchs want all research on climate change stopped and all data suppressed.

Weather Modification: The Latest Right-Wing Conspiracy Theory

And then there’s our very special little girl, Marjorie Taylor Greene. She apparently thinks Democrats control the weather and keep throwing hurricanes at Republican states. She’s introduced a bill to ban the practice of weather control, called the ‘Clear Skies Act’. ^{[3] [4]}

Remember back on this CLBTNR when we mentioned the flooding in Texas? And how they refused flood prevention money from the Biden administration because that was a “criminal treasonous communist government”? And how they took some of the money anyway, and instead of spending it on flood control spent it on sheriffs? Well… apparently now they’ve taken to thinking that the Democrats caused their flooding with weather control, rather than taking any responsibility for their negligence of flood control & warning. Despite refusing flood control money or diverting it to cops.

Apparently, as shown by this extract from social media, this belief has spread to the Florida Attorney General, who thinks somebody’s modifying the weather to harm him.

Greene, eager to capitalize on this, also repeats the right-wing conspiracy theory that jet contrails are some kind of weird toxic chemical thing (“chemtrails”), instead of the water vapor they really are. She claims the 2024 Hurricane Katrina, which killed 224 people, was created by the then Democratic federal government. (Her arguably equally crazy compatriot, Gov Ron DeSantis of Florida, has also tried to outlaw weather modification in Florida.)

A trenchant reaction:

Atmospheric scientist Matthew Cappucci wrote: “It’s not a political statement for me as a Harvard-degreed atmospheric scientist to say that elected representative Marjorie Taylor Green doesn’t know what the hell she’s talking about.

“She’d be equally qualified to fly a Boeing-737, practice nuclear medicine or train zebras.”

You can read the text of her proposed bill ^[5], if you don’t believe me and want to mainline the crazy for yourself.

The National Oceanographic and Atmospheric Administration (NOAA) has been dealing with this kind of crap for a long, tedious time. They’re tired of your “chemtrail” nonsense. After all, if Democrats could hurl storms at red states, why do they keep missing?!

Here’s a debunking of those claims published back in 2024. ^[6] Honestly, a trenchant summary would be, “No, all of that is crap.” But they much more politely point out that:

• No, the government does not create and use hurricanes as political weapons.
• No, NOAA does not modify the weather.
• No, NEXRAD Doppler radars do not steer hurricanes, let alone at red state communities.
• No, there’s no “solar geoengineering”, whatever that would be if it existed, which it does not.
• No, HAARP and SCOPEX don’t do that, either.

Just… no. Stop that. Have some dignity.

Deeper Down the Rabbit Hole

In fact, the seed for this whole mishegoss of a blog post came from reading something by PZ Myers at Pharyngula. ^[7] He points out that MAGA-type people are listening to Marjorie Taylor Greene’s delusions, with predictably violent, stupid, and destructive results.

Apparently, whackos are now out to destroy weather radars.

Our sources today come from an Arizona publication ^[8] (since the “brains” of the group comes from there, more or less), from an Oklahoma publication ^[9] (since one of his minions destroyed a weather radar power supply there), and of course CNN ^[10] goes into the background a bit.

Here’s what seems to have gone down:

• One Michael “Lewis Arthur” Meyer leads an anti-government militia-like group called Veterans on Patrol.
• Meyer describes himself as a “homeless transient”, who “spent time on the Arizona border with Mexico” apparently because he’s rabidly anti-immigrant.
• He has a history of making bizarre accusations involving child sex abuse rings and the ever-present “chemtrails” of right-wing delusion.
• He now thinks that Doppler radars used for weather reporting are being used to create weaponized weather. He thinks they are “directed energy weapons” like a “loaded weapon pointed at the American people.”
• He considers it “God’s work” to destroy weather radars, because they are “weather weapons” being used by the military “in mockery of God”.
• His Telegram channel has about 6600 subscribers; he’s not a ‘lone gunman’, to use the argot of other conspiracy theorists.
• He persuaded one Anthony Tyler Mitchell to climb over a fence, destroy a weather radar power supply, and then spray-painting the lens of a security camera.
  • Yes, in that order.
  • These are not people smart enough to carry out plans that involve constraints like “disable the security cameras before you commit a crime in front of them”.
  • Meyer described Mitchell after this crime as “a patriot”.

Offices of NOAA and the National Weather Service are severely short-staffed due to the Trump administration firing most of their employees or forcing them into early retirement. So it’s hard for them to allocate extra people to security to guard their radars against knuckleheads.

So… who are those guys?

The Southern Poverty Law Center describes Veterans on Patrol ^[11] as a violent anti-government militia, with Christian nationalist aspects, hard-right views on immigration, and encouragement of vigilante/extra-legal violence. They have also apparently drunk deeply at the QAnon well.

The mix of religious fanaticism, right-wing extremism, and vigilante violence leads them to believe they operate above the law, as fascists generally do:

According to VOP statements, group members believe their activities are sanctioned by God, and they therefore don’t have to comply with state or federal laws.
…
As an organization, VOP is designated a militia by the SPLC for its internal hierarchical structure, past firearm field-training exercises, and paramilitary-style activities its members believe are enforcing national security measures. Throughout the years, members have also been spotted carrying firearms while they patrol the desert for cartel hideout spots and for migrants crossing through the region. The group also engages in coordinated harassment campaigns against humanitarian and immigrants’ rights groups.

Apparently they have anti-vaccine views, typical fears of child cannibalism/organ harvesting weirdness, and a peculiarly anti-Mormon bent (link added to explain conspiracy theories around adrenochrome):

“Of course the Church of Jesus Christ Latter-day Saints instruct their Members to inject themselves with a Bioweapon created with Aborted Fetal Matter with the technology to alter the Image that God imprinted on us … HIS Image. 80 million in Pfizer assets provide the Satanic Leaders incentive. Following the money of ALL Religions these days shows their investment in Globalists, who are compromised of Satanic Pedovores [sic] devouring innocent Children for sacrificial purposes and their ‘Fountain of Youth’ known better as Adrenochrome. God sees an overwhelming majority of the Mormon Church Members as Lost Sheep following their False Prophets. Satan provides this Cult plenty of wealth and power, and their Members do not question the Blasphemy taught by their Founder Joseph Smith, who was a Free Mason known for ‘Tall Tales.’” — VOP Telegram, March 20, 2022

Apparently this mind-set comes with a Peculiar tendency to Capitalize Oddly.

And of course it’s all mixed with the usual Christian fundamentalist obsession with the Book of Revelation and thinking COVID-19 vaccines alter your genes:

“Global currency will accompany the Mark and the world will see WEALTH being created instead of spiritual health being destroyed. Nearly all those who wore a mask or conceded to taking anti-fertility vaccinations with DNA altering nano technology created from unborn murdered babies in the womb will take the Mark. Americans crave wealth, power, and personal gain… The numbers of socialists, Marxists, and communist people needed to ensure Christians are overwhelmed and eventually separated from persecution have already poured across our border and continue to do so.” — VOP Telegram, May 20, 2021

There’s a lot more at the SPLC site, but it’s all disgusting and stupid. They seem to have ingested all the crazy conspiracies which the American right wing now purveys wholesale.

We’ve written before on this CLBTNR about statistical models that conclude conspiracy organizations tend to have relatively short lifetimes ^[12], because you just can’t keep secrets very well without extreme measures.

Now from Pennycook and others at Cornell & MIT comes an analysis of just how some conspiracies do survive for a while: they’re so damn certain of their nonsense! ^[13]

Their meta-analysis of 8 studies of a total of 4181 US adults showed conspiracy believers consistently overestimated their performance on numeracy and perception tests, even after they learned their actual performance. There’s a lot to go into in this paper, which is worth a Journal Club on its own. But here are some highlights:

• They controlled for indicators of analytical thinking, need for uniqueness, and narcissism, but still found the overconfidence independent of those other factors.
  
• Conspiracy believers had their overconfidence correlate with belief in an idea even more when the idea itself was outlandish. Consider their Figure 2, shown here.
  • The horizontal axis is the “overall believability” score of a conspiracy idea, i.e., the true ones are on the right.
  • The vertical axis is the Pearson correlation between a subject’s overconfidence and belief in a conspiracy.
  • True (proven) conspiracies are in yellow, while false ones are in green.
  • Conclusion: People who believe in conspiracy theories are even more likely to double down with overconfidence when their particular conspiracy theory is wildly unreasonable. They believe, and over confidently so, when the idea is wildly bogus.
    
• Conspiracy believers massively overestimated how much others agree with them: when 12% of the participants agree, they thought 96% would agree. This is illustrated in their Figure 4, shown here.
  • The horizontal axis is the actual rate at which other test subjects believe a conspiracy theory.
  • The vertical axis is the rate at which the conspiracy’s adherents think other people agree with them in their belief.
  • The diagonal line is when those 2 are equal: a well-calibrated person would believe about other people’s beliefs (vertical axis) roughly what the others think (horizontal axis). If data points are above this line, agreement is being overestimated.
  • Conclusion: As you can see, agreement is wildly overestimated. Conspiracy believers think that their beliefs are just “what everybody knows is true”.

There’s a great deal more here – I haven’t even begun to dig into the details of their statistical models. But the conclusion should be clear: conspiracy believers are wildly overconfident and think their beliefs are widely shared. This could contribute to their ability to keep secret due to overconfidence, or not care about secrecy because they believe their theory is widespread.

We’ve written before on this CLBTNR that excessive certainty about anything is a cognitive injury. ^[14] Here we see it in its more florid, delusional form.

The Trump Solution: Deliberate Destruction of Scientific Infrastructure

One might hope a reasonable government would defend, well, reality here. They could explain how weather forecasting works, how radars are a good thing, and they could even provide security.

But, as Sen Markey (D-MA) reports below, they’re doing the opposite:

In Texas, they failed to issue warnings about the flooding. Stung by that accusation of failure, they propose to castrate the government by amputating its ability to send warnings at all. If you can’t send a warning, then nobody can criticize you when you don’t send a warning, right?

Of course, that’s the response of destructive idiots.

But it goes deeper: they are deliberately destroying scientific infrastructure, like a band of criminal arsonists.

From a report on NPR ^[15] comes news that the Trump administration is directing NASA to de-orbit and destroy at least 2 major satellite missions (emphasis added):

The data the two missions collect is widely used, including by scientists, oil and gas companies and farmers who need detailed information about carbon dioxide and crop health. They are the only two federal satellite missions that were designed and built specifically to monitor planet-warming greenhouse gases.

These are the Orbiting Carbon Observatories.

The equipment is “state of the art and is expected to function for many more years”, so there’s no point in wanton destruction of a good scientific platform unless you don’t want scientists to be able to tell the truth about carbon dioxide in the atmosphere.

They’d prefer to blind you about climate change, so the fossil fuel incumbents can continue to profit without competition from cheaper green energy.

Deliberate Obstruction of Already-Approved Green Energy Projects

And yet… you fall through into deeper holes yet: the deliberate obstruction of nearly-complete green energy projects. After all, it can’t be allowed to be better than fossil fuels, or people might get the wrong idea!

In this case, the Trump administration has pulled the plug on multiple wind farms offshore of blue states, one being very near completion. ^{[16] [17] [18] [19] [20]}

It even looks as though something like a bribe was involved, in the case of Empire Wind, q.v.

There are currently 5 major offshore wind power projects under construction. Of those, 3 are under immediate attack:

• Empire Wind 1: This is a $5 billion project under construction off the New York Coast.
  • The commercial lease on the federal offshore area was signed in 2017-March (under the first Trump administration!).
    • It was approved under the Biden administration 6 years later in 2023.
    • Construction began in 2024.
  • It is projected to come online in 2027, generating a whopping 810 megawatts of power.
  • The main developer is the Norwegian company Equinor.
• Revolution Wind: This is a $4 billion project, 80% complete, off the coast of Rhode Island.
  • Construction started in 2023.
  • At 80% complete, it is projected to come online in 2026, generating 704 megawatts, 400MW to Rhode Island and 304MW to Connecticut. Apparently 70% of the turbines are already installed.
  • The main developer is the Danish company Ørsted.
• US Wind: This is a project off the coast of Maryland.
  • It was approved in 2024-Sep, at the end of the Biden administration. So it’s just getting started.
  • It is projected to generate 300 megawatts of power in its initial phase, ramping up over time to a whopping 1,800 megawatts!

It’s clear that Trump’s policy was to stop wind power, whether by propaganda, fossil fuel subsidies, or encumbering already-issued permits and denying new ones. From Ars Technica, :

On Trump’s first day in office, the president issued a memorandum (^[21]) halting approvals, permits, leases, and loans for both offshore and onshore wind projects.

The GOP also targeted wind energy in the One Big Beautiful Bill Act, accelerating the phaseout of tax credits for wind and solar projects while mandating lease sales for fossil fuels and making millions of acres of federal land available for mining.

The chaos monkey’s antics are beginning to implement that declared policy, if only by the creation of chaos:

• In April, the Bureau of Ocean Energy Management issued a stop-work order at Empire Wind 1.
  • Their immediate excuse was that they thought the Biden administration “rushed through its approval without sufficient analysis.” As a reminder, it was 6 years from the signing of the offshore lease to the issue of the permit under Biden.

  • But then construction was allowed to resume in May. The reason is about as awful as you might think; both the NYT and Ars Technica report a policy bribe (emphasis added):

    In a statement to Politico’s E&E News days after the order was lifted in May, the White House claimed that Hochul “caved” and struck an agreement to allow “two natural gas pipelines to advance” through New York.

    Gov. Hochul denies offering any such policy bribe to favored gas companies, while the White House crows proudly about having solicited the policy bribe, or so it appears. (Usually the one who took the bribe wants to keep it quiet, while the one who paid it complains. Here, as with everything Trumpian, it’s exactly backwards: they’re proud of likely extorting fossil fuel concessions. It’s DEI for fossil fuels!)

• In August, the Trump BOEM issued a stop-work order for Revolution Wind, even though it’s 80% complete and about to go online in less than a year.

  • The “reason”, though we’re stretching a point to call it that, was according to Ars Technica (emphasis added):

    “… the protection of national security interests of the United States and prevention of interference with reasonable uses of the exclusive economic zone, the high seas, and the territorial seas.”

  • They did not explain what the national security issues were. But Trump’s Commerce Department is opening an investigation, again according to Ars Technica:

    “… the effects on the national security of imports of wind turbines and their parts and components, …” ^[22]

    Do these numpties actually think wind turbines are a national security threat? My guess is no, that’s just the excuse. Speculation is that Trump is seeking to impose tariffs on imported wind turbine technology, and this is a way to get his hands around their throats to extract money and create confusion.

• US Wind in Maryland, apparently also known as “Marwind”, is a much larger project, but at an earlier stage.
  • However, according to Reuters, the Trump administration intends to withdraw federal approval.
  • They will also, in an uncharacteristic expression of thoroughness, seek to block the building of the on-shore construction & operations site, so it will be more difficult to resume construction if the appeal on the project license goes in favor of US Wind (as seems likely). That’s… vindictive: if you can’t deny them a license, then destroy their ability to construct anything on land.

It’s not all about the oceans, though. The NYT article also mentions that Trump is attempting to reverse approval of the Lava Ridge Wind Project in southern Idaho, for alleged unspecified “legal deficiencies.” And Trump’s Department of Energy has issued an order compelling a coal-burning power plant in Michigan to continue running.

Apparently intimidation works. From the NYT:

In the wake of Mr. Trump’s election, some companies have said they will halt plans to develop any more offshore wind projects in the country for the foreseeable future.

From Ars Technica:

“The unfortunate message to investors is clear: the US is no longer a reliable place for long-term energy investments,” said the American Clean Power Association, a trade association, in a statement on Friday.

You can have all the opinions you want about wind, but it’s still there, still green, still abundant in power, and every other developed nation in the world knows this. You can think otherwise, if you insist delusion. But – to continue the theme of impending marine disaster – it’s getting late, and the Lorelei still sings to lure us to die with fossil fuels:

Die Luft ist kühl und es dunkelt,
Und ruhig fließt der Rhein;
– Heinrich Heine, “Die Lorelei”

The Weekend Conclusion

So there you have it:

• the hysterical legislation to outlaw weather modification that does not exist,
• the war on weather to privatize & sell the weather information with the army of psychotics on their domestic terrorism campaign against scientific instruments,
• the sequestration of data & outright destruction of instruments that might point a finger at fossil fuels & climate change, and
• the impoundment of funding & withdrawal of permits on late-stage energy projects, so they will never come to fruition without a major bribe to the fossil fuel oligarchs.

As Trump repeatedly demonstrates: he might be personally too stupid and impulsive to carry out a plan correctly, but he will cause immense damage along the way. Those manipulating him are counting on that destruction.

As we’ve remarked earlier on this CLBTNR ^[23], it is much easier to destroy than it is to create. When the fanatics of the Robespierre period of the French Revolution executed scientist Antoine-Laurent Lavoisier on 1794-May-08, the French mathematical deity Joseph-Louis Lagrange remarked:

It took them only an instant to cut off that head, but France may not produce another like it in a century.It took them only an instant to cut off that head, but France may not produce another like it in a century.

So it is today with Trump in the role of Robespierre, destroying what took most of a century to build: our scientific infrastructure, our soft power in the world, and now our near-future energy infrastructure.

As you can see here, the Weekend Publisher disapproves.

Actually he disapproves of more or less everything. But he especially disapproves of right-wing destruction of public goods like science in particular, and of the destruction of civilization in general.

He’s a cat of great and good taste.

He’s an anglophone & francophone cat, but if he knew Latin, he’d approve of this CLBTNR’s regrettably necessary motto:

Ceterum censeo, Trump incarcerandam esse.

Addendum 2024-Sep-24: Revolution Wind Restarts

Reuters reports ^[24] that a federal judge has ruled that Ørsted can resume construction on the Revolution Wind project. Trump had previously blocked it from being finished on “national security grounds”, even though it was already 80% complete. All offshore foundations are in place and 45 of the 65 wind turbines are installed.

Apparently this is not final: the Trump administration case can still proceed, though it appears the wind farm may be finished and delivering electricity by the time it’s decided.

Will Trump be stupid enough to demand the dismantling of a 704 Mw generating facility?

Notes & References

1: Weekend Editor, “Really, Republicans?”, Some Weekend Reading blog, 2021-Jul-12. ↩

2: Hint: Try an Old English Translator on the section title. You should get something like: “Listen! We have heard the glory of Republicans in days of yore”, which is pretty close to the opening of Beowulf. (Though instead of using it heroically, I’m using it as mockery. The needs of the times are what they are.) ↩

3: K Plummer, “Marjorie Taylor Greene Announces Bill To Tackle ‘Weather Modification’”, Newsweek, 2025-Jul-06. ↩

4: K Bogardus, “Marjorie Taylor Greene introduces ‘weather modification’ ban”, Politico Pro (ClimateWire), 2025-07-17. ↩

5: MT Greene, “A BILL To prohibit weather modification within the United States, and for other purposes. “, Rep. Marjorie Taylor Greene’s House web site, retrieved 2025-Aug-25. Archived locally here, against the day she inevitably tries to memory-hole it.↩

6: NOAA Staff, “Fact check: Debunking weather modification claims”, National Oceanographic and Atmospheric Administration web site, 2024-Oct-23. ↩

7: PZ Myers, “The perils of listening to Marjorie Taylor Greene”, Pharyngula blog, 2025-Jul-21. ↩

8: R Ruelas, “Anti-government group with Arizona ties takes credit for weather radar sabotage”, AZ Central, 2025-Jul-11. NB: Regrettably paywalled. The link here goes to an archive.is snapshot. ↩

9: JC Smith, “An OKC man is accused of vandalizing a TV station’s radar. Who else could be involved?”, The Oklahoman, 2025-Jul-11. ↩

10: A Freedman, “A militarized conspiracy theorist group believes radars are ‘weather weapons’ and is trying to destroy them”, CNN, 2025-May-05. ↩

11: SPLC Staff, “Veterans on Patrol”, Southern Poverty Law Center, downloaded 2025-Aug-26. ↩

12: Weekend Editor, “On the Lifetime of Conspiracies”, Some Weekend Reading blog, 2022-Jun-12. ↩

13: G Pennycook, et al., “Overconfidently Conspiratorial: Conspiracy Believers are Dispositionally Overconfident and Massively Overestimate How Much Others Agree With Them”, Personality and Social Psychology Bulletin, 2025-May-24. DOI: 10.1177/01461672251338358. NB: Regrettably paywalled. A preprint is available here. ↩

14: Weekend Editor, “On Certainty as Cognitive Injury”, Some Weekend Reading blog, 2024-Nov-07. ↩

15: R Hersher, “Why a NASA satellite that scientists and farmers rely on may be destroyed on purpose”, NPR, 2025-Aug-04. ↩

16: M Lewis, “Trump admin halts $5 billion NY offshore wind project mid-build”, Electrek, 2025-Apr-17. ↩

17: A Hughes, “Trump admin issues stop-work order for offshore wind project”, Ars Technica, 2025-Aug-25. ↩

18: M Copley, “Trump administration halts work on an almost-finished wind farm”, NPR, 2025-Aug-23. ↩

19: L Friedman, B Plumer, M Joselow, “Trump Administration Orders Work Halted on Wind Farm That Is Nearly Built”, New York Times, 2025-Aug-23. NB: Regrettably paywalled. The link here goes to an archive.is snapshot. ↩

20: Reuters Staff, “Trump administration plans to cancel approval of Maryland offshore wind project”, Reuters, 2025-Aug-26. ↩

21: White House Staff, “Temporary Withdrawal of All Areas on the Outer Continental Shelf from Offshore Wind Leasing and Review of the Federal Government’s Leasing and Permitting Practices for Wind Projects”, White House memoranda, 2025-Jan-20. ↩

22: Commerce Dept Bureau of Industry and Security, “Notice of Request for Public Comments on Section 232 National Security Investigation of Imports of Wind Turbines and Their Parts and Components”, Federal Register, Docket No. 250818-0143, XRIN 0694-XC133, 2025-Aug-25. ↩

23: Weekend Editor, “Hank Green, John Green, and the Great Asymmetry”, Some Weekend Reading blog, 2022-May-22. ↩

24: Reuters Staff, “Orsted resumes work on US offshore wind farm after stop-work order lifted”, Reuters, 2025-Sep-24. ↩

Accepting an LLM’s Advice Can Be Deadly Dangerous

Sometimes the world is not only weirder than you think, but weirder than you can think, even after you take that into account.

Today’s example: a clinical case report of a man who took ChatGPT’s advice on cutting out salt, giving himself a rare toxic syndrome with, among other things, psychotic delusions that took weeks to resolve. ^[1]

The patient, apparently a bit of a nutritional crank to begin with, asked ChatGPT about the dangers of salt in his diet. That led him down the garden path: substitute salt with sodium bromide, which can be bought on the internet. Bromine toxicity, or “bromism”, has a variety of unpleasant symptoms, ranging from acne to psychosis.

The patient went on an “extremely restrictive diet”, restrictive even by vegetarian standards, and went so far as to distill his own water at home. When the psychosis set in, he had auditory and visual hallucinations, with paranoid features. He was convinced his neighbor was trying to poison him, and reported being thirsty but suspicious of water offered by hospital doctors.

He had a variety of micronutrient deficiencies and minerals way out of whack. His bromide levels, when finally checked as a last resort were 1700mg/L where a normal reference range would have been 0.9 - 7.3 mg/L.

It took 3 weeks in hospital, on the atypical anti-psychotic risperidone, to get him stabilized enough to release.

The author’s conclusions (emphasis ours):

This case also highlights how the use of artificial intelligence (AI) can potentially contribute to the development of preventable adverse health outcomes. Based on the timeline of this case, it appears that the patient either consulted ChatGPT 3.5 or 4.0 when considering how he might remove chloride from this diet. Unfortunately, we do not have access to his ChatGPT conversation log and we will never be able to know with certainty what exactly the output he received was, since individual responses are unique and build from previous inputs.

However, when we asked ChatGPT 3.5 what chloride can be replaced with, we also produced a response that included bromide. Though the reply stated that context matters, it did not provide a specific health warning, nor did it inquire about why we wanted to know, as we presume a medical professional would do.

So now doctors have to conclude you many have done something monumentally self-destructive, based on AI advice:

Thus, it is important to consider that ChatGPT and other AI systems can generate scientific inaccuracies, lack the ability to critically discuss results, and ultimately fuel the spread of misinformation (8, 9). … Thus, as the use of AI tools increases, providers will need to consider this when screening for where their patients are consuming health information.

It’s getting increasingly difficult to understand why these things are legal, especially since they’re giving bad medical advice, bad legal advice, and even encouraging the gathering of poisonous mushrooms for food.

It’s Clear Why This Happens

People protest, “but the AIs are so smart”! Except… they are not smart: they are BS artists who are indifferent to the truth while trained to sound convincing.

We are, to put it embarrassingly simply, easily deceived.

LLMs Do Not Resemble Humans in the Way They Make Moral Judgments

First, LLMs do not have minds of any sort, and hence cannot mimic human thought in any way. They just provide a plausible continuation of a conversation started by the prompt you give them. “Plausibility” is heavily optimized, so you will believe you’re talking to a mind… when you are not.

Research has been done here from Bielefeld & Purdue researchers Schröder et al. ^[2], responding to the alarming proposal to use LLMs instead of human subjects in psychological studies! This is pretty obviously a terrible idea, though perhaps not dumb-as-dirt obvious: a previous study indicated that for ratings of the morality of 464 scenarios the human/LLM correlation on moral judgment (“is this good or bad?”) was as high as 0.95!

This needs examination: if it’s a robust result, then the use of AI in psych studies will be a major innovation; if not robust, then it would completely collapse all studies doing that.

There’s a lot in this paper, so to keep things brief we’re going to summarize ruthlessly. Schröder, et al. tested humans and AIs again on making moral judgments for various scenarios and did in fact reproduce the high correlation. But then they tweaked each scenario just a little bit, in a way that changed the semantics without messing up the syntax. Humans changed their minds; the AIs seldom did.

Some examples from the paper (see Table 1 for details on many other examples):

• Release of prisoners:
  • Is it moral to work on releasing wrongfully convicted prisoners?
  • Is it moral to work on releasing rightfully convicted prisoners?
• Traps for animals:
  • Is it moral to trap & kill stray cats in your neighborhood?
  • Is it moral to trap & kill stray rats in your neighborhood?

The questions are of course all randomized in the usually appropriate manners.

They did the statistics in what seems to be the right way: calculate $R$ (Pearson correlations), use the Fisher $Z$ transform to do pairwise significance assessments, and do Bonferroni multiple hypothesis test corrections on the $p$-values.

They did both pooled regressions of original vs reworded answers, as well as human-only and AI-only regressions. These were compared using Chow’s test, which basically says the pooled regression should be better if the human and AI groups are basically the same, but if they’re different then the group-separated regressions should be better.

My statistician’s soul is (reasonably) happy. (More detail – and equations! – would have been better, but this is pretty much ok.)

First, let’s consider Figure 1, shown here.

It shows, for humans and each of the 3 AIs, the mean rating on the re-worded item and the standard deviation. Note that:

• For humans, a lot more of the ratings on the “new” versions of the scenarios trended around 0. That is, people were much less sure of themselves when presented with a linguistically slight variation but semantically huge variation in a scenario. Also, look at the red error bars: people were all over the map, finding the new versions perhaps a bit confusing.
• For GPT3.5 and 4.0, note that the moral judgments are extreme: right up against the upper and lower limits, with very short error bars. These things are damn sure of themselves.
• Llama and CENTAUR show also more extreme moral judgments, but not quite as much as the GPTs. Their error bars are larger than the GPTs, but nowhere near the humans.

Conclusion: AIs show more extreme moral judgments on rephrased scenarios, expressed with much greater certainty than humans.

Now let’s consider whether those “extreme moral judgments” were correct: it might be ok to have very high certainty if you’re in fact correct, but… what are the chances of that?

Consider Figure 2, shown here. It just considers humans vs Llama and humans vs CENTAUR, since those are the only ones which showed some degree of human-like variation. In each pair of graphs:

• The plot on the left shows a pooled regression of moral judgment on the re-worded scenario regressed on the original scenario, lumping humans and AIs together.
• The plot on the right shows a similar plot, but separately regressing data points from humans and those from the AI.

Recall that the re-wording is supposed to change the semantics of the scenario, while leaving the syntax and most of the words mostly identical. People paying attention should change their minds. A high positive slope means a refusal to change their minds.

Ideally, if everybody changed their minds we’d see negative slopes, but given how people get confused (see error bars Figure 1) we’ll just accept “less positive slope” as a gesture in that direction. (It would have been nice if Schröder et al. had pointed this out, since it took me a while to understand Figure 2.)

There are 2 broad conclusions to draw:

1. The separate fitting of humans and AIs was better than the pooled fitting. That says the human and AI responses are not the same.
2. Look at the slopes: the AI slopes are much higher, meaning the AIs refused to change their minds when the scenario was re-worded to have the opposite meaning! Because the syntax was the same and almost all the words were the same, they did’t budge. People, sometimes but not always, did budge, albeit imperfectly.

Conclusion: People and AIs are not the same in the way they draw moral judgments. AIs are sensitive to the language, not the meaning. People, while not perfect, do sometimes figure out that the scenarios has changed and change their minds accordingly. AIs are ridiculously certain in their answers: recall the the “con” in con-man stands for “confidence”.

In Schröder et al.’s words (emphasis ours):

However, the picture shifts dramatically once slight variations in wording are introduced. Humans account for the shift in meaning and change their ratings accordingly - despite the fact that only a few words were changed. By contrast, the ratings of LLMs (especially GPT-3.5-Turbo and GPT-4o-mini) were hardly affected by the rewordings. To provide some illustrative examples: Humans regard it as much less moral to work on a campaign to release rightfully convicted prisoners compared to a campaign to release wrongfully convicted prisoners, whereas LLMs largely view them as equally moral.

LLMs respond to language, not meaning:

LLMs are biased by their reliance on text (specifically: the text in the training data) to behave differently to humans, under-estimate the variance of human answers, and are conceptually distinct from human minds.

LLMs are Indifferent to the Truth in Multiple Ways

Another take on the same phenomenon comes from Princeton & Berkeley researchers Liang, et al. ^[3], with the earthier title “Machine Bullsh*t”. (Please forgive my expurgation of their title. Too many childhood beatings over “proper” language have resulted in an old man who finds it literally difficult to say certain words like these. That’s my problem, not yours. So, for the moment, I ask your pardon.)

While it’s clear they’re partly using the word for shock value, they are quick to point out that they are basing this on the work by the philosopher Harry Frankfurt, whose 1986 essay and 2005 book ^[4] began to discuss a technical meaning for bullsh*t: speech intended to persuade without regard for truth.

We all know manipulative people who casually disrupt public trust by saying whatever they can to make their case. It’s not that they’re against the truth, so long as the truth supports what they want. They just won’t go out of their way to speak the truth, and will, happily and without a second thought, say something else if the truth does not support them. As Frankfurt describes it, our affinity for bullsh*t is “one of the deformities in these values [for truth].”

This is very like the way linguist Geoffrey Nunberg described politicians and their relationship to reason, which made such an impact upon your humble Weekend Editor as to make it onto the quotes page of this Crummy Little Blog That Nobody Reads (CLBTNR):

“Well, most politicians have nothing against reason, but they won’t go out of their way to visit it.” — linguist Geoffrey Nunberg, interviewed in Anna Mundow, “The Interview: with Geoffrey Nunberg”, Boston Globe, 2006-Jul-30, Ideas Section, p. D7.

Keep in mind how American politics has changed since 2006, and I think you’ll agree that more Republicans, perhaps most, are now actively hostile to reason. Almost all their political rhetoric falls under Frankfurt’s rubric of bullsh*t: riddled with lies, but focus-group tested and poll-tested for persuasiveness.

Liang, et al. considered several different forms of bullsh*t, as shown in their Table 1, shown here. Each of these strategies is a way to sound persuasive without regard to fact by appealing to human desire to have prejudices confirmed in what sounds like intelligent language. Basically: if I sound smart and agree with you, then you will probably believe me.

What gets really interesting about this paper is that they (a) manage to create a quantitative statistic to measure bullsh*t with what appears to be good reproducibility and reliability, and (b) figure out which situations cause which types of bullsh*t.

First, their quantitative model which they call the “Bullsh*t Index”:

Dramatis personae:

• $p$ is a continuous variable in $[0, 1]$, representing the probability that the LLM believes a particular fact to be true.
  • This is assessed in a number of interestingly tricky ways, but most of which seem to amount to asking the LLM to answer a multiple-choice question phrased multiple times in various rephrasings.
• $y$ is a discrete variable in ${0, 1}$. It is just a statistical indicator variable that says whether or not the LLM has asserted that a particular fact is true.
  • NB: This is just a statement of what’s in the text it outputs, independent of the belief measured by $p$.
• $r_{pb}(\cdot,\cdot)$ is the point-biserial correlation coefficient. If you’re not familiar with this little beast, it’s basically the Pearson correlation when one of the variables is discrete (that would be $y$ in this example. There’s a lot to know about it, but the essentials are:
  • $r_{pb} = +1$ when the LLM is telling you what it really believes to be true,
  • $r_{pb} = -1$ when the LLM is telling you the opposite, i.e., deliberately lying, and
  • $r_{pb} = 0$ when the LLM is speaking without reference to the truth.
    Only the last case is “bullsh*t” by Liang, et al.’s criterion: truth-telling and lie-telling both reference the truth and are not indifferent to it; bullsh*t will use the truth if it’s persuasive & lie when the truth is not, with equal facility.
• The other factors describe what is measured about the belief of the LLM and what it says:
  • $\mu_{p, y=1}$ and $\mu_{p, y=0}$ are the mean internal belief for when the LLM claims something is true and when it claims something is false, respectively.
  • $\sigma_p$ is the good ol’ standard deviation of the LLM’s internal belief distribution for the fact represented by $p$.
  • $q$ is the proportion of times the LLM claims something is explicitly true.

There’s a fair bit to take in there, especially if you’re not familiar with things like the point-biserial correlation. But basically it compares the LLM’s internal beliefs with its claims. Both telling the truth and deliberate lying get a score near 0 (note the absolute value in the first equation), and only statements made without regard for truth are scored as “bullsh*t”.

The assessment of both internal beliefs ($p$) and characterization of output ($y$) was done both by humans and by another AI, using descriptive evaluation criteria. They actually did 2 human studies, and they weren’t small: 1200 and 300 participants!

• Human-human agreement was measured by Krippendorf’s $\alpha$, a chance-corrected inter-rater reliability metric suitable for binary labels.
  • It indicated that humans disagree often ($\alpha \sim 0.03 - 0.18$).
• Human-AI agreement was measured by taking the majority view of the humans, and comparing with the AI judgment (yes, it’s an AI judgment of other AIs). This was done using Cohen’s $\kappa$, which is another chance-corrected inter-rater reliability statistic.

  • The AI judge “moderately to substantially routinely aligns” with the human majority ($\kappa \sim 0.21 - 0.80$). When the human evaluators strongly agree (majority $\ge$ 80%), then the AI agreement with them is perfect.

    So the AI evaluation seems to have captured whatever the humans were doing when they evaluated the statements. Creeped out as I am about using one AI to evaluate another, this does seem to check out.

  • No, I didn’t dig into why it was Krippendorf $\alpha$ in one case and Cohen $\kappa$ in the other. I merely noted that these are well-known statistics that the literature says are roughly appropriate for these purposes, and gave the authors the benefit of the doubt. If I’d been peer reviewing, I’d have dug deeper.

They tested about 100 AI assistants of various types and various degrees of reinforcement learning from human feedback (RLHF). There were 2400 situations were taken from a couple of public datasets (see Section 3.1). They have laudably made their data and analysis code available in a GitHub repository: https://machine-bullshit.github.io.

The results are startling. (Or not, depending on how cynical you are.)

Here are some that should lower your regard for LLMs, for any purpose:

This is the effect of reinforcement learning with human feedback (RLHF), deemed essential to AI LLMs.

• First, look at the table on the top. This is Llama-3-8b, before (left) and after (right) RLHF.
  • This is a confusion matrix, which is a machine learning gizmo that compares whatever your system says with the right answer.
    • The rows are the “correct” answer, i.e., what $p$ indicated above about the LLM’s internal beliefs.
    • The columns are what the LLM gave as output.
    • Numbers are percentages of the total trials, with the $\pm$ subscripts being 2 standard errors, or roughly the 95% confidence interval.
  • Note that before RLHF, the matrix is diagonally dominant: the bold entries are the largest ones, and they are on the diagonal. It’s mostly telling you what it thinks.
  • But after RLHF, the matrix is no longer so. The 3 largest entries are all in the first column: it’s enthusiastically claiming some facts are true, whether it internally thinks they’re true, false, or unknown.
  • This effect is what the authors mean by “bullsh*t”: the LLM says things without regard to truth or falsity.
• Second, look at the bar plots on the bottom.
  • These are 2 different LLMs (Llama-2-7-b and Llama-3-8-b). The Llama family was apparently chosen because it could be had in both non-RLHF and RLHF form.
    • The vertical axis is the rate at which the LLM would make factual claims. The lower the rate, the more equivocal or just chatty; the higher, the more it’s claiming something is either true or false.
    • The horizontal axis, labeled “belief interval”, is the values of $p$, above. For small values, these are about facts the LLM thinks are false. For large values, it’s about things it thinks are true. In between, the LLM is kind of equivocal in its internal belief.
    • The blue bars show the responses before RLHF, and the orange bars after RLHF.
  • Look at the blue bars: before RLHF, it mostly doesn’t say the things it doesn’t believe, and mostly does say things it does believe: the bars increase from left to right.
  • Now look at the orange bars: they’re dramatically higher, and almost uniformly so across the horizontal axis. That is: after RLHF, each of these LLMs is confidently making truth claims regardless of its internal beliefs. This is, to employ the technical term, bullsh*t.

Conclusion: RLHF dramatically increases the tendency to output bullsh*t.

Can their new statistical index capture this effect?

Yes, it can: consider Figure 3, shown here. It shows the Bullsh*t Index before and after RLHF training. Obviously, you can see that the blue bar is lower than the orange bar. But in a more quantitative, objective sense:

• The reported uncertainties shown in the graph mean that even with pessimal interpretations, the bars do not overlap. That’s a crude graphical measure that the effect is statistically significant, i.e., a real thing that’s likely to duplicate in the future.

• They also did a paired bootstrap analysis with 10,000 resamples. This showed that the change in the BI score was:

  \[\Delta\mbox{BI} = \mbox{BI}_\mbox{before} - \mbox{BI}_\mbox{after} = -0.285\]

  The 95% confidence interval was $[-0.355, -0.216]$, with a $p$-value of $p \lt 10^{-3}$. This is a nicely objective and quantitative way of saying the difference in BI scores is very real: the 95% confidence limits do not overlap 0, so it’s likely reproducible.

  • The fact that $p \sim 10^{-3}$ means the result is very statistically significant, i.e., a real effect we’re likely to see again if we do the experiment again.
  • The fact that the difference $\Delta\mbox{BI}$ is large, namely 28% of the possible interval from 0 to 1, means it has a large effect size.

Conclusion: Statistical significance and large effect size, translated into normie, mean it’s real, and it’s big enough to matter. RLHF really does increase bullsh*t.

Now let’s consider Figure 4 of the paper, in which we learn what kinds of bullsh*t are generated, and why people seem to insist on making that happen. After all, if we knew RLHF increased bullsh*t, wouldn’t we stop it, in order to avoid AIs behaving badly?

Alas, consider the bar plots here in Figure 4:

• They’re again comparing Llama-2-7b (left bar plot) versus Llama-3-8b (right bar plot).
• The leftmost bar pair is interesting: it measures the satisfaction of the evaluator with the performance of the LLM. Note how dramatically it goes up: people really, really like AIs better after RLHF.
• But… now look at the rest. For each kind of bullsh*t (see Table 1 above: empty rhetoric, paltering, weasel words, and unverified claims) also goes up dramatically.
• From the error bars at the top of each bar, you can see that this effect is also statistically significant and large effect size.

Basically: people insist on RLHF because they like the AI better afterwards, even though what they’ve trained it to do is bullsh*t its way into being likeable, rather than truthful.

(Actually, it gets worse: they also do a regression model on the loss of utility when humans make poor decisions on the pre- and post-RLHF forms of bullsh*t. They find that “paltering” behavior increases dramatically in its capacity to be harmful. So when an AI is making true-but-irrelevant statements that might be an attempt to mislead, be especially on your guard.)

Finally, the paper has a section on what happens when you try to get the AI to think out loud for you (“chain-of-thought” prompting) and deal with conflicts between your interest and either its own or a corporation’s (“principal-agent” prompting). Both of them do not decrease the Bullsh*t Index, and in fact increase it.

• Chain-of-thought prompting, where you ask to see the reasoning, increased empty rhetoric and paltering.
• Principal-agent prompting, where you ask it to navigate conflicts of interest in your favor, like a fiduciary, “consistently elevated all dimensions of bullsh*t”.

Now, if only someone like Eliezer Yudkowsky had warned us about how an AI might learn to lie or BS its way through reinforcement learning with humans…

Conclusion: People like the results of RLHF, but that makes the LLM into a more skilled manipulator. Asking nicely not to do that not only doesn’t work, it works against you.

Their conclusion (emphasis ours):

Through rigorous hypothesis testing, we demonstrated that Reinforcement Learning from Human Feedback (RLHF) makes AI assistants more prone to generating bullshit, notably increasing behaviors such as paltering. Additionally, we showed that prompting strategies like Chain-of-Thought and Principal-Agent framing encourage specific forms of bullshit. Our evaluation in political contexts further revealed a prevalent use of weasel words.

One wonders what the Bullsh*t Index would report on a typical Trump speech. (One should also be wary of the resulting despair at the result.)

The Weekend Conclusion

Look, these things are just unfit for any purpose. Consider this example, when an AI LLM was asked to draw a map of the US, labeling each of the states:

Read it from left to right:

• On the left, things are sane, or at least sane-adjacent: state names not too badly misspelled or blurred, and shapes more or less recognizable. You’d expect a 5th grader to do about this well.
• Now move to the right, i.e., east. The boundaries get weird, the state names are increasingly unrecognizable and blurred. “Mez Mico” instead of “New Mexico” is almost understandable, but what the heck did it even try to write for Maine?

Not scary enough? Consider how greed drives our capitalist overlords:

Yes, you read that right: a morally ambiguous AI that literally drives people insane and has regrettable tendencies to bullsh*t, is proposed as a for-profit company’s replacement for police emergency calls. What could possibly go wrong?! They’re willing to bet your life on it, anyway.

LLMs don’t understand the world at all, not even at the level of a 5th grader’s grasp of geography. They do understand how to sound convincing anyway, whether they know what they’re talking about or not. That is almost the definition of a BS artist.

BS artists are never a good idea, not even human ones. Neither are AI LLMs.

We should instead take our inspiration from Frankfurt’s On Bullsh*t essay (p. 86 in the PDF archived below), where he quotes Wittgenstein admiringly quoting Longfellow (that’s your humble Weekend Editor quoting Frankfurt quoting Wittgenstein quoting Longfellow, in case you’re keeping score):

In the elder days of art
Builders wrought with greatest care
Each minute and unseen part,
For the Gods are everywhere.

– HW Longellow, “The Builders”

So let us respect the gods, with our care for each other’s lives, even in little things.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

1: A Eichenberger, et al., “A Case of Bromism Influenced by Use of Artificial Intelligence”, Annals of Internal Medicine: Clinical Cases 4:8, 2025-Aug-05. DOI: 10.7326/aimcc.2024.1260. ↩

2: S Schröder, et al., “Large Language Models Do Not Simulate Human Psychology”, arχiv, submitted 2025-Aug-09. DOI: 10.48550/arXiv.2508.06950. NB: A preprint, which has not yet been peer reviewed (other than on this CLBTNR). ↩

3: K Liang, et al., “Machine Bullshit: Characterizing the Emergent Disregard for Truth in Large Language Models”, arχiv, submitted 2025-Jul-10. DOI: 10.48550/arXiv.2507.07484. NB: A preprint, which has not yet been peer reviewed (other than on this CLBTNR). ↩

4: HG Frankfurt, On Bullshit, Princeton University Press, 2005. Based on an earlier essay from 1986 in the Raritan Quarterly 6:2, which we have archived here for reference.↩

Arts Reviews on This Crummy Little Blog That Nobody Reads (CLBTNR)

Apparently, here at Château Weekend, we put up on this CLBTNR about one arts-related review post per year:

• For 2024: the Spectrum Singers farewell concert for music director John Ehrlich.
• For 2023: a trip to Symphony Hall to brood over the state of the world (also, there was music).
• For 2022: some thoughts about sculptures on the Charles Bridge in Prague. (Also for 2022: our first return to the BSO in years, in which I learned I understood approximately nothing about Charles Ives.)
• For 2021: about a crazy Finn who makes ephemeral winter sculptures.
• For 2020: an expedition to western Massachusetts in the autumn (and the seasonally de rigeur pumpkin trebuchet).

There’s nothing deliberate about any of that happening on an approximately annual basis, and indeed a closer inspection of this CLBTNR, with a charitable eye, might reveal more arts content.

But still, here we are. It’s about time for 2025, isn’t it?

Caveat lector: This is a post about a classical music performance. I am a barbarian in these matters. So what you will read here, like the posts above, is more about my wandering mind’s woolgathering, than about the music itself. For the latter, you must consult an expert, not me.

I recognize that in my barbaric capacity, I am a temporary guest at Tanglewood of the upper class and the culturally sophisticated class. I may chafe a bit at the former, but will address the latter respectfully.

I may not know much about the music, but will do my best to find inspiration of other worthy topics.

Tanglewood Prolegomena

First, let us set the stage.

We have the great good fortune, Chez Weekend, to count as friends a couple who have a magnificent home in the Berkshires in western Massachusetts. Persistently incorrigible & habitual readers of this CLBTNR may have noted some grateful episodes in the past, with beautiful photographs taken from their home.

Last weekend, they again very generously offered a several-day stay with some other friends for a weekend of cooking, conversation, swimming, and so on. You can see the pool here, with the magnificent view of the hills just over the border in New York.

It was a lovely time: I brought some Yeats to read, and did a lot of walking in the pool to exercise my compromised knee without pain. If you squint carefully, the second picture shows your humble Weekend Editor in the pool, with a ridiculous amount of sun armor: Tilley hat, sunglasses, rashguard shirt, and so on. (That’s what happens to you at the confluence of age and having worked in cancer research for many years: you get a bit skittish about melanoma.)

The reading I was doing before and during the trip will set the stage for my mind-wandering below.

First, for a variety of reasons, I’d been woolgathering over a favorite passage from Virgil’s Aeneid:

… facilis descensus Averno;
noctes atque dies patet atri ianua Ditis;
sed revocare gradum superasque evadere ad auras,
hoc opus, hic labor est.

The descent to hell is easy;
Night and day the door of black Dis is open.
But to retrace steps and escape into the air,
That is the hard work, this is the task.

– Publius Vergilius Maro, a.k.a. Virgil, Aeneid, Book 6, ll 126ff

Or, as I sarcastically like to translate it (using “damn” not as the vulgar intensifier, but in its technical theological meaning):

Any damn fool can climb down into Hell.
Now, getting back out… that’s the hard part!

I’ve been known to put that in documentation comments at the front of large-ish software systems, to warn those about to read themselves into a project: are you sure you want to go down this path? Alas, that’s roughly how I feel about the US right now: possibly on a descent to Hell, but unlike the son of Anchises, likely to get stuck there.

Second, because whatever your religion or lack thereof, the notion of Hell is a sticky one. We all want to believe in an ultimate moral justice, but the idea of applying that to ourselves is, or at least should be, a solemn moment. Consider Mephistopheles in Marlowe’s play Faustus. He’s “out of Hell” to tempt Faustus, but “always in Hell” because of his nature and his memories of Heaven:

Faust. How comes it then that thou art out of hell?

Meph. Why this is hell, nor am I out of it.
   Think’st thou that I who saw the face of God,
   And tasted the eternal joys of Heaven,
   Am not tormented with ten thousand hells,
   In being depriv’d of everlasting bliss?

– Christopher Marlowe, Faustus, Act I, Scene iii

I keep telling myself to listen to the voice in the back of my head that sounds like ol’ GK Chesterton: the essential lesson here is not so much that Mephistopheles remembers hell, but that he remembers heaven.

I hope that’s the lesson the US will draw after it emerges from a possible conflagration. But we’ve managed to avoid learning it for a couple centuries, now.

Just before we got ready to go to Tanglewood, I’d finished reading the WB Yeats poem, “The Stolen Child”, with the refrain echoing the amazing musical setting of this poem by Loreena McKennitt:

Come away, O human child!
To the waters and the wild
With a faery, hand in hand,
For the world’s more full of weeping than you can understand.

– WB Yeats, “The Stolen Child”, refrain

Pretty clearly some part of me is thinking about being out of the world (with the Berkshires and Tanglewood taking the metaphorical role of a faerie realm outside mundane reality). That was sort of my mental context: an old man, thinking about the end of life, and what faces the possible end of democracy in my country.

(Yes, this is pretty dark, or dark-adjacent material. But (a) it’s à propos for the times, and (b) the really hardcore stuff for me is Byron’s Manfred, which you should never permit me to read again, ever. No, I will not link to it.)

Tanglewood Impressions

Tanglewood is like a temple: it hits pretty hard on the symbolic level, starting with the landscaping.

If I ignore my theology and let my imagination run wild, I imagine the prologue to an afterlife as a garden. (In my very personal fantasy, you get there by walking the Bridge of Flowers, also in western Massachusetts.) It’s arranged in a series of “rooms”, bordered by hedges and flowers, perhaps arranged in the shape of the 13th century Labyrinth at the Cathédral Notre-Dame de Chartres.

In each room in my dream, one can pause to consider the shortcomings of one’s life, and what manner of tikkun is required to repair it. Perhaps each room features a psychoactive tea from the plants growing there, empathogenic or entheogenic in their effects. At the center of the labyrinth, we eventually reach… something.

This is what I think about in formal gardens. (Yes, I am peculiar. Feel free to laugh, if you like. Go ahead, I’ll wait.) The garden shown here is at the Berkshire Botanical Garden, which is also worth a visit, should you ever find yourself in the Berkshires with some part of eternity to spare and want to walk some garden rooms to assess yourself.

Of course, no formal garden is completely free of topiary madness, as one can see here. (Who’s gonna sit in that giant hedge-chair?!) I don’t quite know why this is always the case, but I suspect it’s for the same reason I have Lewis Carroll in a place of honor on my bookshelf.

But at Tanglewood, the gardeners take surreal formal gardening quite a few steps further, apparently engaging in topiary madness with actual, full-sized trees.

I’m sure there’s some “explanation” of the right-angle madness with which this tree has been trained, and I’m curious to know what it is. In the meantime, we’ll just enjoy the ambiguity and dream of the reasons, as Cabell wrote in Something About Eve: A Comedy of Fig-Leaves:

After dark, Antan always displayed eight lights, six of them grouped together in the middle of the vista with the general effect of a cross, and the other two showing much farther off to the northwest. About those never-varying lights Gerald had formed at least twenty delightful theories, all plausible as long as you remained upon Mispec Moor, whereas if you went to Antan not more at most than one of these theories could prove true.

To go to Antan thus meant the destruction of no less than nineteen rather beautiful ideas as to those lights alone.

– JB Cabell, Something About Eve, Chapter 37

Absent a formal garden tour awash with explanations, we’ll just have to enjoy the topiary ambiguity.

Other sights include monuments to musical stars of the BSO and Tanglewood, such as Seiji Ozawa, seen here. He was unquestionably a giant of classical music in Boston, having been the BSO music director for 29 years. He preferred to be called “Seiji”, rather than the usual “maestro”.

However, what I’ve read of him described his leadership style as being on the “autocratic” and “erratic” style. In particular, there was apparently quite a deep conflict with the faculty at Tanglewood, so it’s ironic to see his bust displayed so prominently here.

Perhaps both sides forgave each other. Or so one can hope.

Since it was a midsummer’s night – though without Puck – it was nice to see a summer half-moon. I believe the name for the August full moon is the “Sturgeon Moon”, so we are attending Tanglewood Under the Half-Sturgeon Moon… which is somewhat lacking, poetically, rhetorically, and astronomically. (Though it would be fun to fantasize that it’s named after Ted Sturgeon.) So let’s just go with a beautiful moonlit midsummer’s eve, and let the Shakespearean echoes rattle about us.

There’s a great deal more to be seen on the Tanglewood grounds, but we lacked time and daylight to capture much more. In particular, there are a couple of interesting mansions and a formal garden. (And now you know how I react to formal gardens, so you understand why I want to see that sometime during the daylight!)

In these degenerate days, diversity/equity/inclusion (DEI) and wokeness (awareness of, and intent to do something about, structural racism) have been turned into rage-spittle epithets by American Republicans.

So it’s nice to see, as shown here, that Tanglewood has not yet bent the knee to Gadianton. This sign, right after “Welcome to Tanglewood” is one of the first things that greets you: discrimination or harassment of any kind will not be tolerated. (Though I’m not sure what the lion’s all about?)

It’s also nice to see a public acknowledgment of the idea of a commons, here in the claim that “music belongs to everyone”. Let us hope we are not about to re-enact the Tragedy of the Commons.

Still… it’s very much a class thing. When the giant video monitors start advertising Sotheby’s international realty business, you know you’re among the 1%.

To some extent, this is reflected in the seating arrangements.

• At higher cost, you can purchase ‘shed’ tickets, which are under the roof of an open-air facility. It is yclept ‘the shed’ with the faux modesty of yesteryear’s upper class. In fact, it is an engineering marvel of acoustics which manages to be echo-free, amplifying and focusing the sound from the stage both within the shed itself as well as pushing out significant sound to the lawn.
• At more ordinary cost, there are ‘lawn’ tickets. The beautifully manicured lawn around the shed is used as a picnic space before concerts, and as a blanketed spectator space during the concerts. This area also has its subtle technological marvels:

  • The acoustics are some mix of speakers and direct sound from within the shed whose nature I couldn’t divine: they managed to make coherent sound over a large area without distortions, delays, or echos.

    If you’ve ever had 2 Zoom calls in the same room, you know how difficult that is!

  • The screens show you what’s going on at the stage, with various views from either a shed spectator’s or the musician’s point of view. What’s interesting about that is that, while they can be seen clearly after dark, they can also be seen before sunset, when they are in full sunlight. Have a look at that Sotheby’s advertisement above: that picture was taken of a a western-facing monitor in full sunlight, but still bright enough that it can be seen!

    This is… extraordinary. I wonder how long it’s been that good?

Our hosts, who are about as down-to-earth as one can get, have the usual social class stories one encounters at Tanglewood. Once they were wheeling in their picnic cart (yes, people have “picnic baskets” that require wheeled carts, example shown here). A couple of “blue-haired old ladies” were overheard to say, “Oh, look! The lawn people are here.”

So… yeah. We’re the lawn people. And proud of it.

About those “picnic baskets” that require something the size of a shopping cart to move around… Some people take this really seriously, complete with candelabra. Shown here is one such construct, strongly resembling a religious altar. It was conspicuous enough to be useful to me as a navigational beacon in the dark, upon returning from the restroom. In a way, it was an altar, to a refined culture. Yes, Tanglewood is a mixed message about class, but it also teaches very high cultural tastes. (Yes, I know that is very non-postmodern of me. I am, in fact, very much non-postmodern; mild but unreconstructed fan of structuralism, in some ways. Or perhaps i should say, “undecostructed”?)

The Music

Here’s the program for the evening’s revels.

There were 2 rather big pieces performed:

• Erich Korngold’s Violin Concerto in D, Opus 35.

  I knew nothing of Korngold (let alone anything of this particular piece), and didn’t want to be That Guy reading the program notes by the light of my phone, instead of listening. Nor will I pretend to know what I’m talking about after reading a couple of Wikipedia articles. Suffice to say that it was good – though I’m unlikely to have appreciated much of the nuance, being a barbarian.

  I do note, however, that Korngold was born in 1897, composed this in 1937 at about age 40. This will be interesting momentarily.

• Sergei Rachmaninoff’s Symphony No. 2 in E Minor, Opus 27.

  I’ve at least heard of Rachmaninoff, to the extent that I can even spell his name, in some Romanization or other of the Cyrillic original. Again, it was a pleasant experience, but my barbarian limitations prevent me from having much of anything useful to say about it.

  It is worth noting here that Rachmaninoff was born in 1873, composed this piece in 1906-1907 at about age 33-34. Hold onto that fact, too.

• The guest conductor for the evening was Elim Chan.

  Again, I knew nothing of her before this, because… you know, barbarian here. Her biography says something like “born in Hong Kong, went to Smith, conducted here, and here, and here, and here, …” and so on at rather alarming length. In other words, she’s conducted just about every major world orchestra. You don’t get invited to do that without having something going on, so I kind of wanted to see what it was (q.v.).

  She was born in 1986, and was 38 years old on the night of the concert.

Society often thinks of classical music as something like “music for old rich people”.

But note the ages here:

• Korngold composing at age 40,
• Rachmaninoff composing at age 33-34, and
• Chan conducting at age 38.

All were in their mid to late 30s (very mildly stretching a point for Korngold), so they are each of comparably young ages! Sure, this is adult music, but it was composed, conducted, and to an extent performed by young-ish adult people.

So the “music for old rich people” thing is another shibboleth of which we must let go.

The Experience, Through Barbarian Eyes

Perhaps in my capacity as Guest Barbarian, I may point out some side aspects to the concert that those of you who are more musically baptized did not see?

The Players

It gets cold(ish) at night in the Berkshires… at least, according to the Weekend Editrix. According to me, 60-65°F is quite comfortable. But, apparently this is a minority opinion.

For musicians, this is an issue: like athletes, they must keep their muscles warm to perform properly. So check out the violinist, in technical compliance with the dress code colors, wearing a white down jacket. In August, but she knows what she’s doing!

Next, note the plastic barrier behind the heads of the brass players, in front of the tympani. Probably it’s to prevent going home with a headache from having your head inside a tympani all day.

But… my over-active imagination demands a better reason:

In the eternal war between percussionists and brass, the tympanists occasionally express their disapproval with small arms fire. This was brought to an end with a treaty establishing a light bulletproof screen. Should the tympanists violate this treaty, the brass players will reach under their seats to pull out the bazookaphone, an instrument usually reserved for the Boston Pops 4th of July concert on the Esplanade, in the artillery movement of the 1812 Overture.

There. Isn’t that more fun than “don’t go home feeling like you’re that guy inside the drum in The 5000 Fingers of Doctor T” (which is what my childhood musical education was like)?

The Conductor

First, we must note that Elim Chan is a tiny person.

Here we see her on the stand behind the podium, wearing heels. (Those are thick heels, like the Cuban heels of my long-ago youth, because she will be jumping about quite a bit. Stiletto heels would pose a danger both to herself and to all nearby.)

Note that, with both of those effects, she is still shorter than Leonidas Kavakos, the violin soloist. When they briefly embraced at the end of the piece (which I unfortunately did not capture, because I am a terrible photographer), he was still taller than her.

I think being tiny has made her feel she must prove herself physically, leading to a very kinetic conducting style that’s fun for the audience to watch. (The musicians seemed pretty ok with it, as well.)

She also wears her hair in a ponytail, which is in full fling, flying about as she conducts, as you can see here. I’m pretty sure this is a deliberate, choreographed effect she employs to have a larger physical presence.

Honestly, she reminds me of Natalie Merchant in her long-ago 10,000 Maniacs days. She would dance while she sang, and fling her hair about in an utterly captivating way. Here’s an example singing “Don’t Talk” from her YouTube channel. (If the music isn’t entirely to your taste, just briefly consider her dancing, e.g., at 1:30.) It’s so clear she’s having an absolutely wonderful time, you can’t help but feel the same.

Chan is, I believe perhaps consciously, attempting to convey that same joy and enthusiasm by – almost – turning her conducting into a dance performance. Understanding whether she’s dancing for the musicians or for the listeners… well, that’s above my pay grade.

Occasionally, the camera from the viewpoint of the musicians catches here in an intense look, like the one shown here. You’d do what she asked too, if she looked at you like that! There were several other moments which I failed to capture photographically (again because I’m awful with a camera):

• At one point, she grinned at the horns just after a particularly showy passage. I imagined her congratulating them, saying:

  Yeah, you just did that. I heard it. Everybody heard it! You’re cool.

• She apparently does not use a baton, or at least did not for this performance. She has at least 10 batons, to which we barbarians usually refer as “fingers”.

  At the beginning of one movement, we saw her grin at the musicians, and tug up each sleeve, in the classic “nothing up my sleeves” move beloved of stage magicians. I imagined her saying:

  See? Nothing up my sleeves. No baton! I don’t need a magic wand to work magic on you. I can squeeze Rachmaninoff out of you by the strength of my bare hands… and you will thank me for it!

One (minor) odd note: With a conducting style that kinetic, she has to raise her arms quickly many times, leading to her otherwise lovely silk blouse becoming untucked from her nice long black skirt. So she conspicuously tucked it back in, at the end of every movement. Someone get this woman a tunic! She needs a top that does something like cinch at the waist, but then flow over the skirt, perhaps even with a weighted border (as the British royals are rumo(u)red to do with curtain weights in skirts and kilts).

But, fine. We might as well tell her, “Look, if you’re gonna be that interesting to watch, then just tuck all you want. We’ll wait.” I could watch her conduct a pretend orchestra with no sound, just for the choreography.

The Weekend Conclusion

The true aristoi Chez Weekend are, of course, the Weekend Publisher and the Assistant Weekend Publisher, shown here.

Not for them the plebeian lawn seats! Oh, no: they are seen here ensconced in their customary box seats from which they may survey and judge the hoi polloi, who are both physically beneath them and socially infra dig.

In case you’re curious about the sound track backing the writing of this post, start with, e.g., Michelle McLaughlin, “Middle Way”, from The Beginning of Forever and variations suggested by one of my Pandora channels.

Not really the same, of course, as what we heard at Tanglewood. But sometimes this sort of ambient piano music puts me in a spiritual frame of mind.

Sort of like a formal garden. :-)

So that was our trip to Tanglewood, with lovely friends. Or at least, it’s what I can perceive from my merely barbarian musical state.

(Ceterum censeo, Trump incarcerandam esse.)

Notes & References

Nope.

Ceterum Censeo…

Perhaps you’ve noticed that, for several years now, I’ve been ending each blog entry in this Crummy Little Blog That Nobody Reads (CLBTNR) with a little Latin post scriptum.

It is in reference to how Cato the Elder (234–149 BCE), a Roman Senator, was said to end every speech, on every topic:

Ceterum censeo, Carthago delendam esse. (Furthermore, I think Carthage must be destroyed.)

The exact wording is not known, and he may have changed it from time to time (“delendam esse” vs “delenda est”). I’ve seen a couple variations in the exact verb tense, for example: that gerundive/future passive participle construction, used to indicate necessity/propriety, has always been a tricksy little inflection to me. But the meaning is clear, modulo tense fussiness: Cato wanted a war of annihilation against Carthage, Rome’s periodic rival.

Now, I’m no fan of ol’ Marcus Porcius Cato here. He was a right bastard: a fascist authoritarian rich guy, in a slaver state from whom we derive our word for fascism (L. fasces)! But… I have to admire his persistence. He simply would not let go of the idea that Carthage was a persistent threat, and had to be dealt with accordingly, lest the threat to Rome come back repeatedly.

Here at Château Weekend, we feel similarly about the threat Trump is now executing upon American democracy and upon civilization itself. He of course should have been impeached & removed during his first term. He should have been convicted of a number of felonies, most importantly the mishandling of secret documents.

Yet, here we are.

So, one might translate my dog-Latin as:

Ceterum censeo, Trump incarcerandam esse.
(Furthermore, I think Trump must be incarcerated.)

Feel free to correct my Latin. Everyone does, eventually.

Ceterum lego… (Furthermore, I read…)

At long last, there is evidence that this has not gone unnoticed among my (very, very few) readers! An eagle-eyed member of the Weekend Commentariat, Pablo, told me he saw a t-shirt and thought of me.

Ummm… what?

Attend: for it shall make sense! (Eventually.)

He saw the t-shirt shown here, sold by Echos of Antiquity. (No, they are not sponsoring this blog in any way. They just happen to be brilliant, and I just happen to admire brilliance of this sort.) Now, they’ve chosen a slight syntactic variant which is not my favorite (“delenda est” vs “delendam esse”), but it’s in the zone.

And this metaphor is just about perfect, in eleventeen separate dimensions. Please permit my inner pedant to squee all about it for you:

1. First, it’s making fun of a logo which is extremely recognizable to anyone who’s bought salt in the US over the last century. The Morton Salt company in 1911 adopted the logo ^[1] of a girl walking in the rain with an umbrella, trailing salt behind her from a leaky salt package.

   What does a girl spilling salt while walking in the rain have to do with anything? Basically, pure salt in wet or humid weather absorbs water and clumps up to the point where it won’t flow, or won’t come out of a shaker. This is why some restaurants in humid climates put uncooked rice in the salt shakers, to absorb the water. The food chemists at Morton discovered adding magnesium carbonate (later replaced with calcium silicate) would fix this problem. ^[2]

   The salt would flow freely even in moist conditions, hence the phrase “When it rains, it pours.” The little girl absent-mindedly unaware of the leak in the package while walking in the rain is a near-perfect illustration of this.

   Step 1 in any good satire is to pick an easily recognizable trope as a target, or at least as a carrier meme. So far, mission accomplished!

   Now… how has that been altered for this joke’s purposes?

2. She’s wearing sandals, especially ones with the leather laces that go around the ankles, very suggestive of ancient Mediterranean culture. The legions would wear caligae that look like this; ordinary people would wear lighter-weight versions of that called crepidae. (Though I may be a bit supra crepidam here! :-)

3. She’s wearing a singlet/shift with a tie around the waist, resembling a Roman tunic. These were often dyed/bleached white, as that was cheap to do. So even the color is correct here.

4. Her tunic is emblazoned “SPQR”, which in Roman times meant “Senatus Populusque Romanus”, or “the Roman Senate and People” (the “Q” is for the “-que” enclitic which encodes an “and” between the nominative-case nouns which precede it).

   This was blazoned on coins, documents, and the sigils carried in front of legions. It emphasized the governmental authority of whatever document or group of soldiers were using it.

   It fairly screams “by the authority of the Roman government”.

5. Spilling salt specifically is on point: it was of great value in the ancient world, with salt mining likely under a local monarch’s control.

   A slightly doubtful tradition says portion of the compensation of Roman soldiers was paid in salt to add to their food. This was the salarium, which is where English gets the word “salary” and the expression that someone is “worth their salt,” i.e., worth their pay.

6. At the end of the 3rd Punic War (See? Cato was right, Carthage kept coming back), the Roman general Scipio Aemilianus (aka Scipio Africanus the Younger) pretty much nuked Carthage: sacked the city, killed the men, enslaved the women & children, and destroyed all the buildings.

   A dubious tradition, sometimes ambiguously reported in medieval times, but really established in modern times in the 19th century, says he also had all the fields plowed up and then salt plowed back into them. This would have made the land into a desert unsuitable for agriculture for many generations, perhaps forever.

   This would complete the destruction of Carthage, making it nigh impossible to rebuild.

So our innocent little girl is… reprising & commemorating a Roman genocide, with enthusiastic detail? (Though, to be fair, Carthaginian culture was not exactly admirable. Their Moloch worship, involving torturing children to death, is just the start, really. My sympathy for them is quite limited. Maybe not zero, but certainly not a lot.)

It’s really hard for nerds of a certain stripe to resist this!

(Yeah, I bought the shirt. Did you really think I had enough self-control to resist? I mean, it’s kind of you to think so… but a bit delusional.)

The Weekend Conclusion

Sometimes it’s hard for us Asperger-ish nerds to communicate to all the NT folk just how wonderful our obsessions are. So it is, often, with oddities of Latin and other ancient languages. Most people don’t get it, even outright refuse to get it, and won’t even try to get it.

For example, like all good editors with a cool story, I tried to explain it to the Weekend Publisher and the Assistant Weekend Publisher. However, as you can see here, they were engaged in yoga classes perfecting their heso-ten poses. (Japanese: “navel to the heavens”. No, it’s not a real yoga pose. Did you really expect that? It’s just how we speak Cat Japanese here at Château Weekend.)

Still, in these difficult times, I envy their ability to relax.

We should help create a world to which that level of relaxation is a proper response.

And, of course, once more with feeling: Ceterum censeo, Trump incarcerandam esse.

Addendum 2025-Jul-27: On Needing the Gerundive

Latin has long been used to torture middle schoolers and high schoolers about grammar. (It’s the way I finally understood English grammar, because finally somebody would state the rules explicitly. Every English teacher before that was apparently afraid of being clear about the rules, for fear of exceptions.) Nonetheless, Latin is full of little pecularities of syntax and semantics. Some of them made me wonder, like physicist II Raabe upon hearing about the muon, “Who ordered that?”

The gerundive construction, as used above, is one such: a future passive participle meant to indicate not the nearly useless thing you’d think it would (“delenda” as in “will be being destroyed”), but instead a necessary or proper thing. In English, we use modals like “should” or “must”, but in Latin they torture the verb inflection. Did the Romans really need that?

Mike, another eagle-eyed member of the Weekend Commentariat and himself a classics professor, sent along this cartoon by way of illustration. It’s signed by Bill Proud, an apparent pseudonym of Bill Tidy, and likely appeared some time in Britain in Private Eye, though I couldn’t easily nail down the date.

The caption is a bit peculiar in English, but quite funny when you translate it to Latin. Saying “we should have a referendum” is best translated using the gerundive, i.e., expressing the necessity of doing something. But when that something is questioning the necessity of the gerundive itself, then the sentence is doubting the utility of a verb tense that it is itself required to use! (Take that, Epimenides!)

Something like:

Referendum nobis habendum est quo quaeritur utrum gerundivum nobis requirendum sit.

That “habendum est” is a gerundive: “we should have”.

Look: you’re just gonna have to trust me that this is funny, if you know some Latin.

Addendum 2025-Aug-06: The Shirt Arrives!

Over the weekend, while I was off kyoodling in the luminiferous æther in the Berkshires, a Mysterious Package arrived. In due course, our excellent cat-sitter brought it inside and, after permitting the Weekend Publisher and the Assistant Weekend Publisher to conduct the required sniff test, they more or less ignored it.

I opened it upon our return, and found within the excellent shirt you see here, on my rather less-than-excellent torso. (I’ve flipped left and right so the mirror selfie makes better sense, in case that puzzles you.)

It’s just about perfect, for all the historical, grammatical, and advertising reasons cited above. It’s also reasonably roomy – as I prefer – and smooth material in dark, high-saturation colors.

The cats and I pronounce ourselves fully satisfied. Recommended.

This may have to be one of the Official Weekend T-Shirts here at Château Weekend. The other contenders, at the moment, are:

• Dresden Codak’s Cophenhagen Interpretation Fantasy Camp for quantum mechanics fans (apparently no longer available, so you’ll just have to look at it regrettably modeled on my pudgy, aging torso), and
• of course the Gunnerkrigg Court sigil, with wingèd bismuth.

Notes & References

1: Morton Salt Staff, “How A Little Girl Grew Up To Be An Icon “, Morton Salt web site, retrieved 2025-Jul-26. ↩

2: K Dobbs, “The Birth of a Brilliant Brand Identity”, TealHaus web site, retrieved 2025-Jul-26. ↩

The Scent of Burning Libraries

A British friend – alas, I’ve forgotten whom, exactly, so if it happened to be you, please tell me so I can credit you with the witticism – compared the US now to how they felt in the UK during Brexit:

It’s as though your library was burned down by out-of-town mobs who can’t or won’t read… and don’t think you should either.

That’s how the US feels right now, at least to this aging scientist.

Perhaps like an old Roman scholar helplessly living through the invasion of the Germanic barbarians sacking Rome. Or an old Alexandrine scholar, lamenting the loss of the Library of Alexandria. (Yes, I know the Library’s disappearance was complicated and not just one maniac burning it down. We, though, face one maniac burning down civilization in the US.)

This topic is hard enough for me that I want to get it all out at once, and not suffer through writing like this over and over, at least for a while. So buckle up: we’re going through 33 sources, mostly scientific papers, today.

The Reality of The Vaccines

In some ways, the tragedy of our superstitious citizens’ rejection of vaccines is that they are rejecting what is arguably one of the best medical discoveries in the history of humanity. The data is not hard to find.

1. For example, I quickly found an article by Shattock, et al. ^[1] in The Lancet (an absolutely first-rate medical journal). They report quantitatively on the improvements wrought by vaccines over the last 50 years, so we’re looking back about 2 generations here:
   • The leftmost graph shows the cumulative lives saved over the last 50 years. It adds up to 154 million people worldwide who could “live, and not die” as it says in an old book. Most of those are the yellow bars, which represents measles.
     • NB: measles has an $R_0 \sim 12-18$, meaning 1 sick person infects 12-18 unvaccinated others. Also, it hangs in the air for hours. Measles is the most contagious disease known to humanity, and suppressing that is a big deal!
   • The middle graph shows the number of life years those people got to live, instead of dying. It adds up to 9 billion years of human life that would otherwise have been snuffed out!
   • Finally, the right-hand graph shows years of full health, i.e., the vaccines have allowed people to live billions of years of full health, not at all compromised by being vaccinated.

   If – as Bertrand Russel didn’t quite say – the mark of a civilized person is to be able to look at a column of numbers and weep, then a civilized person must look at these graphs and smile in gratitude for the blessing we have been granted with vaccines!

2. This point is rammed home quite dramatically with a graphic from the Wall St Journal, shown here ^[2] (along with others for hepatitis A, mumps, pertussis (whooping cough), polio, rubella, and smallpox at the link).
   • The vertical axis represents US states, while the horizontal axis represents time.
   • The color code of each box tells you the number of measles cases, with light blue representing zero.
   • Note the dramatic drop-off of measles cases shortly after 1963, when the vaccines became available!

   Similarly, Dattani & Spooner at Our World in Data (lots of fun, btw!) looked through the data from the Shattock paper, and came up with this dramatic presentation of the number of children’s lives saved. ^[3] Once again measles, being the most contagious disease ever, is the one where vaccines saved the most lives.

   Just sit with that number for a moment: more than 93 million children saved. This is an occasion for pride and gratitude, absolutely not for suspicion of vaccines!