I am extremely grateful for the publication of this result.

Why? Because it means this method has gone mainstream and replications can flourish by using it.

So, here's the first replication, all using the U.K. Biobank. This is for Black-White differences in IQ:

https://twitter.com/cremieuxrecueil/status/1966156734680150379

Notes!

0. The sample for the population result is *everyone* with ≥1/16 and ≤15/16 African admixture, the within-family result is for the siblings among them. I didn't plot between-families results, but they're pulled from the same distribution as the population result, so when I have those computed I'll replot, but they shouldn't be any different (will take a few hours, maybe be tomorrow, w/e).

1. Yes, datasets will be merged and sharper results will be obtained for the article on this that's coming out ~shortly. Can't be done for all phenotypes in the UKBB, but can be done for IQ at least. For example, we don't have lipoprotein(a) (lp(a)) measurements in some of the samples of young American kids, some of them don't have objective skin color measurements, etc. As a side note, this result holds up with brain size (not shown) in the UKBB, but I'm unsure if it holds up in the young samples that'll be merged with it, as they're still developing in most cases.

Anyway, the IQ p-value is p = 0.008 (two-tailed) within families and extremely low between them. The within-family result is robust, will get sharper with more data, and is also sharpened by using a latent variable instead of a score, and by correcting for measurement error (not needed with the LVM). Score shown for simplicity and ease of others with UKBB access replicating this. Also, accounting for error in the admixture computation, the p-value would drop a bit further, but not by very much since error is very small.

2. The "IQ per unit of admixture" is statistically indistinguishable between the population and within-family results, and yes, it explains most of the Black-White difference in IQ. I just wanted comparably-scaled results for all the traits here, so you're seeing r's. It's pleasant that the within-family variance reductions aren't enormous for siblings, which is what we expect even with quite high heritabilities given their genetic relatedness. It's the same result we've seen with American data, and it's also nice to see that in the case of this trait, the global admixture result *can* be interpreted like the within-family one. Presumably this only holds with measurement invariance, as we see in the U.K. when comparing Whites and Blacks there. Since we see this in the U.S. too, it's likely that the previous, already-published within-family null—which had a sizable effect in the correct direction which also could not be distinguished from the global r—was just a false-negative.

3. This result replicates with other degrees of relatedness, but we might lose the causal interpretation with those ones because the estimand for, say, a cousin test is different given the identity of the "C" variance component shifts for that comparison.

4. What is architectural sparsity and why is it relevant? Consider this table from nature.com/articles/s4159… (cc: @hsu_steve):

Basically, sparsity refers to the number of variants involved in a trait. It also refers to their effect size distribution. So, for Alzheimer's, for example, the trait is highly polygenic, but APOE explains more variance than the entire rest of the PGS, so while being under highly polygenic control, it remains moderately sparse.

If you're still not grokking what I mean here, consider some distributions of cumulative effects across the chromosomes. Here's the result for lp(a), which is already known to be influenced by essentially one gene. Guess which chromosome it's located on:

Consider, as a comparison, creatinine, which is considerably less sparse, and thus has effects distributed across all chromosomes:

Now, consider what this does to within-family admixture assessments. Skin color, for example, is controlled by only a handful of genes. This means that global admixture shouldn't tag it very much between siblings. The same is even more true for lp(a). And in fact, now we have confirmation of this!

But, we know from other methods that lp(a) is effectively entirely genetically-caused between populations. This is just accepted within the medical community because it is an obvious fact that follows from its strong control by a single gene. You can also figure this out using local ancestry estimates. Basically, the correlation between genome-wide ancestry and ancestry at a causal loci is what we want to get at, and if you know the causal loci, you gain power by restricting your analysis to that area. This is what we find with lp(a) (not shown, but use your brain. The obviousness of this fact is why the author used lp(a) as an example).

Also, in some sense, the frequency of that locus between ancestries gives you what you need without doing all this within-family stuff, if you're confident it's causal. The effect estimate might still be biased by population structure though, so that's worth keeping in mind.

There will be a post soon with more details and the expanded set of results with the additional datasets, robustness tests, and plenty of other fun things to look at.

TL;DR: this is a spoiler, and it shows that, yes, you can explain the Black-White IQ difference in Britain mostly genetically, and the global admixture result that I've posted here before is equivalent to the within-family one. Woohoo for things that should hold up, in fact, holding up!

As a sort of replication of the Young paper, you cannot explain the difference in educational attainment (as years of education) in this way. Why? Well, hard to say. Compensatory factors like I found with the GCSEs? (Haven't read that post yet? Go check it out here: cremieux.xyz/p/explaining-a…). Poor phenotype quality? Very plausible, because education really is a huge garbage heap, but why would that be in the general population and not within families? Maybe it has to do with what other traits admixture tags? Maybe it does replicate, but we just can't see it, because the precision is too poor (possibly the lp(a) story too). Who knows!

Q: Will the combination with more datasets allow us to fix this educational attainment result?

A: No, because most of the other datasets involve young people, not people who have almost all completed their educations, as in the UKBB. That plus the generational change and international incomparability in the definition of educational attainment makes it too poor as a phenotype. Sorry!

Any questions?

Link to a fun previous post from the same dataset, showing a result that *does* hold up within families: x.com/cremieuxrecuei…

Link to another post mentioning the forthcoming article earlier: x.com/cremieuxrecuei…

Ever wondered why advertisements heavily feature Black actors when they're just 12-14% of the population?

I might have an explanation:

Black viewers have a strong preference for seeing other Blacks in media, whereas Whites have no racial preferences. These results are derived from a meta-analysis of 57 pre-2000 and 112 post-2000 effect sizes for Blacks alongside 76 and 87 such effect sizes for Whites.

If you look at them, you'll notice that Whites' initial, slight preference declined and maybe reversed.

You're on trial, and the jury can't make up their minds. The decision is a coin flip: 50/50, you either get it or you don't.

Your odds of a given verdict depend on the "peers" making up your jury.

If you're Black and they're Black, your odds are good; if you're White, pray. Though White jurors have, on average, no racial bias, the same can't be said for Black jurors.

Where the White jury gives you approximately the coin flip you deserve, the Black jury's odds for a verdict are like a coin rigged to come up heads 62% of the time.

Posts saying Charlie said things he didn't, oftentimes even including videos where he doesn't say what the post says he does, have convinced me.

There will be no organic temperature-lowering coming from the left, because they don't want it.

They believe the things they claim. They actually believe the people they dislike *are* racists, fascists, homophobes, transphobes, all of it.

They are not reasonable, and they cannot form anything like a reasoned argument for these perceptions.

Even still, it's really what they think.

Your child's teacher says that people like you deserve to be killed for your beliefs.

They also laughed at the fact that when people like you are killed, their kids lose a parent, because again, 'people like you deserve it'.

You believe the teacher should be: An airline pilot said that people like you should be killed for your beliefs.

You believe the pilot should be:

A few days ago, I posted this image.

It shows that the gender wage gap is mostly about married men and their exceptional earnings.

In this thread, I'm going to explain why married men earn so much more than everyone else🧵 The question is:

Does marriage maketh man?

Or

Are all the good men married?

That is, does marriage lead men to earn more, or do men who earn more get married more often?

I've seen a lot of people wondering why America has such a high incarceration rate.

If you weren't even aware that it does, consider this graph from Prison Policy:

To understand why America is like this, consider that, when Stalin died, his secret police chief Lavrentiy Beria released more than a million non-political prisoners and the result was a massive crime wave.

This is not the only instance of this happening in history. Plenty of places have done large-scale prisoner releases, and they nearly universally have the same effects wherever they happen: crime goes up.

One of my favorite examples comes from Italy.

On July 31st, 2006, the Italian Parliament passed the Collective Clemency Bill. This bill reduced the sentences of eligible inmates convicted prior to May 2nd, 2006 by three years, effective August 1st, 2006. As a result, thousands of inmates were released immediately. In fact, 83% of all releases through December, 2007, happened in August, 2006.

The pardon was motivated by the activism of the Catholic Church, including personal involvement from Pope John Paul II. The Catholics argued that prisons were overfilled, holding people in crowded conditions was inhumane, and a release was needed. They also had historical precedent on their side: after the second World War, there were regular collective pardons in Italy, but they stopped in 1992 after a parliamentary change, making the 2006 pardon the first of its kind in fourteen odd years.

Researchers Buonanno & Raphael documented what happened when the pardon went into effect. First, take a look at the incarceration rates over time:

Prior to the pardon, incarceration rates were trending up fairly slowly.

Afterwards, they trended up at a much more rapid rate!

In fact, the incarceration rate converged back to roughly where the whole thing started after less than three years. By December 2008, it had reached a rate of 98 again, compared to 103 in August of 2006.

The reason why the incarceration rate rapidly returned to the level it was initially at isn't terribly shocking: it's because crime increased!

In response to a major increase in crime, police had to start arresting more people. Recidivists and those otherwise driven to crime by the release of so many criminals needed to be arrested or the crime spree would have carried on.

In other words, incarceration incapacitates criminals, and when you shock the incarceration rate by releasing tons of criminals from a state of being incapacitated, crime goes up until they're put back in jail.

Well, unless you're fine living with a higher crime rate. If you are, then the incarceration rate can remain at a lower level.

There's a tradeoff here: if country A has a population that tends to commit few crimes regardless of policy, they can have low incarceration rates. But if country B has a population that tends to commit many crimes regardless of policy, they'll have to settle for having higher incapacitation rates if they want to realize crime levels like country A.

The populations differ in terms of antecedents of crime, so the treatment of those populations has to differ if they're going to achieve the same results.

This clears up why America has such a high incarceration rate: it's because Americans are relatively violent people!

This also tells us why El Salvador's efforts have been such a success. But before being explicit about that, here's another result from Buonanno & Raphael.

Leveraging cross-province differences in the numbers of people pardoned, they found that incapacitation effects on crime were larger when the province had a lower pre-pardon incarceration rate! Or in other words, there were diminishing returns to increased incarceration!

The reason for this is that the population is constantly in flux. There's growth, there's immigration and emigration, there's death—people come and go. There'll always be someone who is going to commit another crime. If we're lucky, there'll also always be someone there to catch them.

Some people commit more crimes than others. If you lock up all of the worst offenders, you can seriously reduce crime. For example,

- In Sweden, 1958-1980, a rigorously enforced three-strike law could have halved violent crime (x.com/cremieuxrecuei…). In this example, it was found that 1% of the Swedish population did 63% of their violent crimes.
- In America, the vast majority of people admitted to state prisons, 2009-2014, were repeat offenders (x.com/cremieuxrecuei…)
- In cities like Chicago, Atlanta, D.C., Portland, and basically everywhere else, homicide victims and offenders tend to have long rap sheets (cremieux.xyz/p/minority-rep…)

These are fairly universal findings! Crime is very concentrated: within regions, within cities, along streets, among a few people, within a few ages. The further down you go, the greater the concentration of crime perpetration in general.

The reason higher pre-pardon incarceration rates meant smaller incapacitation effects was because the worst offenders tended to be locked up already in those areas. Accordingly, if you lock up the marginal offender in a high incarceration area, you prevent fewer crimes from happening compared to if you lock up Vincenzo Megamurderer who has a rap sheet longer than a foot race.

And this replicates!

- Vollaard found that a 2001 law passed in the Netherlands that handed down ten times longer sentences to prolific offenders reduced rates of theft by 25%. This was subject to diminishing returns: as municipalities dipped deeper into the pool of repeat offenders in applying repeat offender sentence enhancements, the incapacitation effect got smaller.
- Johnson & Raphael found that between 1978 and 1990 in the U.S., each additional prison year served prevented 14 serious crimes. At the time, the average incarceration rate was 186 per 100,000. In the period 1991 through 2004, each additional prison year served prevented was just 3, and 2.6 of those being property crimes. In this period, the average incarceration rate was 396 per 100,000. America had hit the point of diminishing returns.

In elasticity terms, the Italian collective pardon revealed a crime-prison elasticity of -0.4, and with dynamic adjustment, they were as high as -0.66.

- Johnson & Raphael found crime-prison elasticities of -0.43 for property crime and -0.79 for violent crime for the 1978-1990 period.
- Levitt used prison overcrowding litigation as an instrument to estimate the crime-prison elasticity with data from the late-1970s through to the early-1990s, and he found elasticities of -0.38 to -0.42 for violent and -0.26 to -0.32 for property crime.
- A year after Buonanno & Raphael's study, Barbarino & Mastrobuoni published their own analysis of Italian collective pardons for the eight pardons laid out in the period 1962-1990. They found an elasticity of total crime ranging between -0.17 and -0.30.
- Buonanno et al. found that, in a comparison of the U.S. and Europe, the crime-prison elasticity was -0.40. They were able to do this estimation because, modern Europe at the time had developed higher property and violent crime rates than the U.S. (excluding homicide), so they exploited panel data on the reversal of misfortunes that implied.

So, back to El Salvador: they currently have the lowest homicide rates in the western hemisphere.

Some people claim they've been on this path since 2015, but it's hard to make this case, when their reversion from that year's peak was consistent with regression to the mean, and regression to the mean does not tend to make things better than ever before. It was very likely the massive lockup of people who were confirmed criminals that has brought El Salvador this level of unprecedented peace.

To put a pin in this: incarceration rates are endogenous!

Different places have different incarceration rates because they have different underlying rates of crime, different levels of and population support for and cooperation with policing, and different tolerances for keeping criminals locked up or set free. Places are in different equilibriums for numerous reasons, which is why comparisons of incarceration, policing, and crime rates are often facially meaningless. It simply makes no sense to make an unqualified statement like 'Incarceration doesn't work - just look at Louisiana, which has both high incarceration and high crime!'

To really understand the linkage between incarceration and crime requires causally informative research like the wonderful work I cited on Italy's collective pardons. To really grasp the thorny issue of crime in general requires plying your counterfactual reasoning skills so that you don't make a silly mistake like saying:

Alaskans wear bigger, puffier, more insulating coats than Floridians, yet they suffer more hypothermia deaths. Therefore, we can reject that view that coats help people to stay warm.

Sources: cremieux.xyz/p/a-twitterx-d…

Bonus! An earlier thread on counterfactual reasoning about a different topic: x.com/cremieuxrecuei…


Bonus post:

You can plausibly trade off policing and incarceration. If you choose to police more, you can incarcerate less with the same crime rate and vice-versa.

https://x.com/cremieuxrecueil/status/1961323064894882143

The days after George Floyd died, Black people started engaging in violence at much higher rates, radically increasing America's murder rate.

In the modern day, I don't know of any other group that reacts to the news this way. We can see this surge in violence at all resolutions.

The surge happened in the week Floyd died.

I tell non-Americans that the United States accounts for:

- About 4% of the global population
- About 13% of global drug consumption
- About 50% of global drug spending

And they're often floored.

For so many drugs, America is *the market*. What's wild is, this isn't alarming because the U.S. is a rich country and medicine is a superior good.

U.S. health spending is in line with its exceptionally high spending in general. Other countries consume about as much as the U.S. did when it was as poor as them.

One of my favorite studies on the validity of psychological measures was a survey that included 15 commonly-used measures.

Virtually all of them were found to be invalid for making comparisons between groups. The only scale passing muster was the Need for Cognition scale.

Measurement invariance was assessed for age and sex and the degree of measurement invariance violations was not computed. That degree could be problematic or fine, but we don't know.

Either way, lots of invalidity.

After I posted this thread, I was given all the raw data.

So, here are the zero-sum moral circles, where the categories are explicitly non-overlapping and giving moral units to a higher category does not include a lower-level category.

First, conservatives: very family-centric!

https://twitter.com/cremieuxrecueil/status/1962314265152332130

In case you're unfamiliar, these are the levels.

Participants were instructed that the moral units to allocate were like currency they can spend on others and allocate to different moral circles, and that a higher-level circle does **not** mean allocating to a lower one.

Here's a fun alternative to the moral heatmap way of getting at in-groups.

Just ask people what communities they identify with most.

Liberals identify with the globe first, the nation second, and their local community last. Conservatives go nation, local, then global.

https://twitter.com/cremieuxrecueil/status/1962314265152332130

This study also gave participants the option to either pocket or donate another $5 for completing the survey.

They were given an international, national, or local charity option.

70% of liberals and 56% of conservatives donated something. Both liked local charity the most.

The moral circles study gave two versions of its circle task:

- One with a limited number of moral units, and thus moral allocation was zero-sum

- One where participants had unlimited moral units to distribute however they liked

Replot thread🧵

Everyone, zero-sum first. The authors provided values on concern for humans versus nonhumans, and the results had to be scaled to be proportional.

Each allocation proportion is treated as a radial coordinate. To give it spread, we assign an angular coordinate θ = π/4 to tilt it like the original.

Cons:

I'm delighted by how upset this benign observation made some people, because the same thing happened with the survivorship airplane meme.

If you're unfamiliar, it's this:

The supposed origin of the image is Abraham Wald's observation that the British Royal Air Force (RAF) was reinforcing the wrong parts of planes that returned from raids on the Germans. The military was noticing where the bullet holes were in planes that returned. The fact that those planes made it back suggested that those areas of the plane were the sturdiest, and reinforcement should instead be done on the areas without bullet holes.

This is a wonderful way to illustrate the concept of survivorship bias. It's so useful that it's come to be the canonical example in many classrooms, and the image has been seen by billions. The image went viral online as a way of illustrating survivorship bias. For example, you'll regularly see the image posted in response to someone making a mistake that's due to a failure to understand survivorship bias.

When this image first started going viral, one of the common responses to it was to state that the image was not, in fact, one ever seen by Wald or used by the RAF, and that it was actually just an illustrative mockup based on another mockup by @cameronmoll from 2005. The issue with that statement is that, after a short while of being viral, almost no one knew the origin of the image, and almost no one claimed it was actually an image used by Wald of anyone in the RAF, so it doesn't matter. The image is still an excellent way to understand survivorship bias.

A good question then, is why anyone would care that this clearly illustrative image wasn't actually used by Wald or the RAF. I'm going to wager that, for most people who made that argument, they were just missing the point. But, for some, they might just be regurgitating what they saw other people saying in response to people who wrongly claimed that it was a diagram used by the RAF. People like to do that—they like to repeat what they believe to be smart arguments, even when the context makes their point irrelevant.

The moral heatmap is in this stage of mimesis, where there's still a large mass of holdouts who haven't accepted that the meme just is the meme regardless of the study the diagram comes from. You see these holdouts everywhere, but as memes spread, they become less common. They exist for scientific papers and even for basic words. Some examples follow:

"Alpha" and "Beta": Supposedly pieces of wolf status hierarchies, these words now just mean you're a "Chad" or a "Virgin", a winner or a loser. The research on wolves didn't work out and the concepts don't hold up there, but it doesn't matter one bit, because these words now have a meaning separate from their misconceived origin. If someone says 'X is alpha!' or 'Y is a beta!' you don't win the argument by saying 'Actually, those parts of wolf status hierarchies don't exist in the real world' you just look retarded, because the words now describe something real: losers and winners! (With some added nuance that comes from sentiment attached to alpha/beta.)

The Dunning-Kruger Effect: This is supposedly the psychological bias where people with low knowledge/ability/awareness/etc. are overconfident. In some permutations, of the phenomenon, experts are underconfident, but it's irrelevant. What people understand the phenomenon to be isn't real: it's a statistical illusion resulting from binning a continuous variable with a raised intercept and an imperfect correlation between confidence and knowledge.

But, if you bring this up to debunk someone saying "Dunning-Kruger" to suggest someone is an overconfident buffoon, you just look retarded, because the words now describe something real.

The Banality of Evil: This is the idea that anyone can be made to do great evil, particularly through the influence of just following directions from authority figures. This was supposed to explain the Holocaust. Banality was supposedly confirmed in a series of experiments that took place at Harvard in the 1960s. In the Milgram experiments, students were told to shock someone they couldn't see, even as the shock intensity kept escalating and the person behind the wall screamed out louder and louder. They supposedly took part in this because the test administrator—an authority figure—was urging them along.

But in reality, the experiments were misdescribed and participants resisted more than Milgram said. Subjects also didn't go along with the experiments nearly as often if they believed them to be real. They also just didn't comply, applying weaker shocks when the experimenter was urging stronger ones.

The Banality of Evil is not real, but it doesn't matter. If you say we know it's not real, you are being retarded, because the concept still has utility in the expanded set of cases it's applied to these days, and in being used as a touchpoint to explain 'going along with orders.'

"Left-Brain/Right-Brain": This is the idea that the left and right hemispheres of the brain divide logical thinking from creative thinking, and that certain personalities have a given dominant hemisphere. The idea is untrue, but if you call this out when someone says something like 'That's very left-brained of you!', then you are being retarded, because left/right brain has entered the popular lexicon and it now refers to personality regardless of if its origins describe some real neural locallization.

"Reptile Brain": Carl Sagan popularized this one. This one comes from a now-discredited model of the evolution of the human brain, from the brain reptiles have—basal ganglia—to one other mammals have, allowing emotion—with the addition of the limbic system—to the one we humans have, allowing higher thought—with the addition of the neocortex.

After Sagan's popularization, people started to use being reptile brained as an insult. You can allege someone's actions are due to their reptile brain, making them a primitive. Though this concept and a lot of its support is now discredited, it led to good theorizing and discoveries, and if you respond to someone saying you're reptile-brained for being dumb, then you are being retarded, because the term now has a separate meaning from the theory it originated from.

"Marshmallow experiments": This refers to a very influential experiment where kids were told they could have a marshmallow now or have two if they waited. The kids who waited were supposedly vastly more successful in life. This is an interesting way of conveying that people who exercise more self-control are likely to be more successful later on. The experiment didn't itself hold up, but people now use the term "Marshmallow experiment" to refer to things where having self-control matters. For example, 'life is a series of marshmallow experiments'. Replying to this by saying that the experiment didn't hold up is retarded, because it's now a shorthand for delayed gratification.

"Lemmings": These cut little animals supposedly jump off of a cliff and kill themselves. But in real life, they don't do that. That was just a myth made by Disney. Nowadays, the name of the animal is often used to refer to people engaging in self-injurious or suicidal behaviors. You can point out that lemmings don't actually kill themselves, but you'll just look retarded, because a 'lemming' now refers to something besides the animal.

"A Frog Doesn't Notice It's Being Boiled": Kind of says it all. They do notice, but it doesn't matter, because when people use this phrase, they're almost never referring to actual frogs being boiled, they're referring to situations where people are haplessly unaware of dangerous changes around them. If you correct people by saying that frogs do notice being boiled, then you looked retarded, because again, that is not what people are really referring to, it is a turn of phrase.

"Eskimo Have 100 Words for Snow": This funny phrase was meant to humorously illustrate cultural relativism, but people started taking it literally. Now it's mostly not used as a fact about Eskimo culture, but as a stand-in for 'cultures vary' and sometimes 'people think too much about what they're overexposed to', and if you point out that the Eskimo don't have all those distinct words for snow when someone uses it like that, you're being retarded.

"You have the memory of a goldfish!": People believe goldfish have short, three-second memories. This isn't true, but it's entered the popular lexicon. If you say someone has the memory of a goldfish, you don't look smart by replying that 'actually, goldfish remember many things in the long term', you just look retarded, because people generally are not referring to actual goldfish memory span, they're saying you have a short memory.

"She's a Type-A personality": Some people have claimed that there are two main personality types: A, and B. Type A personalities are ambitious, competitive, and thrive under pressure, while Type B personalities are relaxed, patient, and adaptable. These don't really exist, but if you correct someone saying that a given person is "Type A" to refer to their ambitious personality, then you are being retarded, because their statement isn't based off of the theory, it's a broad description of a person's perceived personality as being a certain way.

Tons of these concepts have proliferated and entered the public consciousness. New ones enter it all the time, and I think we should generally welcome them if the concept has a real referent worth being able to talk about more clearly, which is what the concepts provide us with. The person who just can't accept this, who has to point out that these things aren't real, just doesn't get that memes evolve. They're the same sort of person who also points out things like:

- People misuse the word "literally"
- People misuse the word "ironic"
- People misuse the word "decimate"
- People misuse the word "peruse"
- People misuse the word "spazz"
- People misuse the word "approximate"
- People misuse the word "nauseous"
- People misuse the word "factoid
- People misuse the word "bigot"
- People misuse the word "nonplussed"
- People misuse the term "begs the question"
- Economists are misusing the word "identification"
- People misuse the term "enormity"
- People REALLY misuse the term "moot point"
- Etc.

But language evolves, and the misuses of literally decimating spazzes help us to understand one another better. They can also help people to signal affiliations, make their use in jokes, etc.

I propose that the people who feel compelled for whatever reason to object to memes and words that've evolved beyond the use they're trying to bring them back to are suffering from dysmimesis. Mimesis refers to the representation of the real world in art and literature—what the moral heatmap now does—and dysmimesis refers to the act of objecting to mimetic drift, or the dispositional urge to protest or 'correct' the evolved use of a meme, word, symbol, or practice as it spreads—i.e., resistance to mimetic/semantic drift and a wish to restore an earlier, 'proper' form.

P.S. I've used the word "retarded" a lot throughout this. It formally refers to people having adaptive behavior deficits, but almost everyone just uses it as a synonym for stupid. If you don't get that, then, well, you're a dysmimetic retard.

More reading on Banality, Marshmallow Experiments: cremieux.xyz/p/the-vast-emp…


Oh, and, yes, I am aware that the rationalist community is a frequent origin for terms like "marshmallow experiments" as they're now used. That's one of the things I like about rats!

There are massive intelligence differences across populations.

https://twitter.com/fchollet/status/1961858122672472400

Also, it only takes twice as long for a variant at a constant selection pressure to reach fixation in a population of 10,000 as in a population of 100.

Where is he getting the idea that 5,000 years is short? With rising populations, that can easily mean accelerated evolution.

The funniest response to the heat map meme is to bring up the study and talk about it showing something else, as if that's relevant.

People posting the meme are almost never talking about the study and its conclusions couldn't matter less for what the meme represents now.


What are some more examples of people getting confused about memes like this?

'The terms [Alpha] and [Beta] are meaningless because wolves don't actually operate like that!' comes to mind.

Complimentary approaches can make this thread's point clear.

So here's an exploration of county-level results🧵

Firstly: We can explain most of the variance in homicides by just using county race shares, and not even getting particularly detailed with them.

https://twitter.com/cremieuxrecueil/status/1961656373009437046

That data came from CDC WONDER.

What if we control for which party governed the states during the time period that data is from?

That adds basically nothing. The benefit of this control is nonsignificant.

Two Democratic governors and tons more Democratic elected officials have been talking about how Red States have more crime and killing.

This is misleading🧵

Let's look at homicides. Using data from the CDC's WONDER I've plotted homicide rates by race and state: If you look down at the bottom of the graph you'll notice the summaries for

- Red States (Republican governors for most years 2018-23)
- Blue States
- The country as a whole

I didn't plot Hispanics because that would've crowded the graph and looked even messier

Let's use this

Crime is way down in D.C.

Is it because the National Guard is arresting tons of people, or something else?

While there have been a lot of arrests, crime is down too much for that to be all.

Let me tell you about one of my favorite crime papers. It's about police presence🧵 In 2010, the British government issued a report. The report held that there was far too much unnecessary spending going on in policing.

As a result, London's Metropolitan Police saw a 29% budget cut.

To save money, the city shut down 70% of its police stations.

Scandinavian countries have extensive population registers that allow them to study complex phenomena with ease.

One example of this is the trans mortality rate.

It's popularly argued that this rate is extreme— >40%! —but this is not true and is exaggerated by confounding🧵

https://twitter.com/cremieuxrecueil/status/1960795470542070218

When we control for the number of prior contacts with psychiatric specialists, we are effectively proxying for one's history and severity of mental illness.

By doing this, researchers found that being referred for gender reasons went from predicting a doubling in risk to...

People so strongly want to believe groups like Italians were considered non-White when they arrived in the U.S. that they will conflate being treated poorly with being treated like they're another race.

Every time I've mentioned this, I've gotten that same asinine response. The people who make this argument seem to desperately want people to think that groups can become White and that the conflicts of the past were all racial.

But no.

The Irish, for example, were disliked more for being corrupt Catholics and public drunks than for being non-White.