How bad are Richard Lynn's 2002 national IQ estimates?
They correlate at r = 0.93 with our current best estimates.
It turns out that they're really not bad, and they don't provide evidence of systematic bias on his part🧵
In this data, Lynn overestimated national IQs relative to the current best estimates by an average of 0.97 points.
The biggest overestimation took place in Latin America, where IQs were overestimated by an average of 4.2 points. Sub-Saharan Africa was underestimated by 1.89 pts.
Bias?
If you look at the plot again, you'll see that I used Lynn's infamously geographically imputed estimates.
That's true! I wanted completeness. What do the non-imputed estimates look like? Similar, but Africa does worse. Lynn's imputation helped Sub-Saharan Africa!
If Lynn was biased, then his bias had minimal effect, and his much-disdained imputation resulted in underperforming Sub-Saharan Africa doing a bit better. Asia also got a boost from imputation.
The evidence that Lynn was systematically biased in favor of Europeans? Not here.
Fast forward to 2012 and Lynn had new estimates that are vastly more consistent with modern ones. In fact, they correlate at 0.96 with 2024's best estimates.
With geographic imputation, the 2012 data minimally underestimates Sub-Saharan Africa and once again, whatever bias there is, is larger with respect to Latin America, overestimating it.
But across all regions, there's just very little average misestimation.
Undo the imputation and, once again... we see that Lynn's preferred methods improved the standing of Sub-Saharan Africans.
There's really just nothing here. Aggregately, Lynn overestimated national IQs by 0.41 points without imputation and 0.51 with. Not much to worry about.
The plain fact is that whatever bias Lynn might have had didn't impact his results much. Rank orders and exact estimates are highly stable across sources and time.
It also might need to be noted: these numbers can theoretically change over time, even if they don't tend to, so this potential evidence for meager bias on Lynn's part in sample selection and against in methods might be due to changes over time in population IQs or data quality.
It might be worth looking into that more, but the possibility of bias is incredibly meager and limited either way, so putting in that effort couldn't reveal much of anything regardless of the direction of any possible revealed bias in the estimates (not to imply bias in estimates means personal biases were responsible, to be clear).
Some people messaged me to say they had issues with interpreting the charts because of problems distinguishing shaded-over colors.
If that sounds like you, don't worry, because here are versions with different layering:
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The White House just released a really good executive order on cleaning up America's streets, re-institutionalizing insane people, and ending open air drug abuse and the problems it creates.
Here's a quick overview🧵
The first section is the one I'm most excited for. An alternative name for it could be "Bring Back The Asylums"
It instructs the administration to make it possible to involuntarily commit crazy people again
That crazy hobo pushing a cart full of urine bottles? He's going away!
The next section is one that you'll need to familiarize yourself with if you're interested in 'what happens next'.
This was a never achieved goal in Trump-I.
The idea is to compel cities to do what you want by withholding, barring, and giving discretionary funds for compliance.
What comes after myostatin inhibitors make everyone buff?
One new candidate is:
Safe, cheap, and easily-administered injections that locally remove fat. A new drug that just passed through phase 2 seems to do just that🧵
The new drug is called CBL-514.
It has a counterpart on the market in the form of deoxycholic acid injections—brand name Kybella.
Kybella is FDA-approved, and it works: it helps people to get rid of their double chins. But there's a catch.
Kybella, unfortunately, is not all that safe, and though many patients swear by it, there are notable side effects.
This is predictable, since the way Kybella works is through cytolysis: causing cells to die by rupturing them, releasing their contents, causing inflammation.
Pseudonyms afforded the protection needed to write things that were controversial, to engender debate over things they didn't themselves believe in, and to encourage focus on ideas over reputations
Thread of their known pseudonyms🧵
Alexander Hamilton, James Madison, and John Jay all wrote under the name Publius, after the Roman consul Publius Valerius Poplicola.
This shared authorship became known after Hamilton died, but the individual authors of the Federalist Papers Publius entries remain debated.
John Jay and John Stevens, Jr. shared the Americanus pseudonym when writing various Federalist essays.
One of my favorite papers in recent years included this diagram.
It shows the impact of controlling for three different types of variables: confounders, colliders, and mediators.
With confounders, control is good. With the others, you ruin your result by controlling.
If you have variables with measurement error, you can run into another problematic variable: the proxy.
Proxy variables can make all of these distortions much worse and much more difficult to deal with.
The paper makes this simple observation: statistical control requires causal justification. That's actually the title.
They gave several DAG-based examples. Consider this one: is edutainment a confounder or a mediator? Should you control for it, or would that bias your estimate?