The establishment's theory of race differences in socially valued metrics is that this is due to "systemic racism", a kind of Marxist conspiracy theory where the dominant group (Whites) keeps other peoples down.
There are clear testable predictions from this theory. In places where racist, White people have more power, outcomes for non-Whites, especially Blacks and Hispanics should be worse. Recall that the US demographics by county look like this.
Of course, Republicans are racist in this theory.
Thus, the theory predicts that in these areas of the USA, Blacks and Hispanics should be particularly worse off compared to Whites. But the exact opposite is actually true. The race gaps are smaller, not larger, in Whiter and more Republican areas.
The above figures are for test score gaps, but the same holds true if we look at social status gaps. Here's some maps of race gaps in social status.
So we need another way to explain the variation in social status gaps. Well, it's easy. Test scores -- academic achievement that mainly reflecting intelligence -- explain why race gaps are smaller and larger in various locations. Meritocracy works.
It gets even worse for the theory. It turns out the effect of White population share and Republican vote share are interactive. The areas with the smallest race gaps are the ones with the largest White populations and the largest Republican vote shares combined!
There we have it. The Marxist conspiracy theory that is the go-to explanation of race relations fails when we look at county-level variation across the United States. The predictions it makes are exactly opposite of reality. If anything, it seems Republican Whites are good for minorities.
If you want more details, read my new blog post:
New study out: Systemic Racism Does Not Explain Variation in Race Gaps on Cognitive Tests
Using data from across the world, we estimated the speed of selection against intelligence across countries.
There is a certain regionality to the data
Relatively atheistic north Europeans have apparently quite weak selection, while more religious areas have stronger negative selection. This is the opposite of what American data suggested when studying individuals.
Some big accounts as asking why so many MAGA types are suddenly so very anti-Indian, considering that Indians in the US and to some degree in the rest of the West, are model immigrants (high performance, low crime). The main answer is not difficult to understand.
This answer is based on the typical finding of sociology. In terms of partisanship, whichever groups in society you dislike is just the ones you perceive to be most different from you politically. Brandt and colleagues worked this out in 2014.
On top of this general pattern, there's the fact that importing a bunch of foreign workers depress local salaries. That is of course why the companies do this. What's the largest source of such foreigners? India. So capitalists love them (cheaper labor) and workers dislike them (suppress their wages).
Maybe you've seen a map like this one. It gives one the impression that Europeans were uniquely or particularly evil regarding slavery, in this case of Africans.
However, slavery was more or less a human universal. Pre-Columbian Americas, ancient China, or the Islamic world.
Europeans, rather than being the master enslavers (which they were also for a time), were rather the liberators. The only group of people who decided to take matters into their hands to free the slaves of the world.
"Once dull, always dull". Special education classes have very good metrics for teacher education and students per teacher, but they don't seem to improve much from this extra effort. So Terman infers from this that these factors cannot be of great importance.
New study of 2700 Indian whole genomes shows that Indo-European/Yamnaya/Steppe is quite low, about 15%. It is a bit higher in the north (almost 20%) and among those who speak IE languages, but not impressively so. Too much mixing since the arrival.
Inbreeding is strong. The median person had identical blocks in their genome at the level suggesting their parents were 3rd cousins, whereas the human average is about close to 4th cousins (Africans less).
Annoyingly, the data is not public, even though American taxpayers paid for this. Can't wait for Trump admin to maybe do something about this abuse (inb4 fell for it again award).
Not everybody commit scientific fraud at the same rate. Let's look at some data. First retraction rates.
We can also look at the top list of most fraudulent researchers ever (so far those that were caught). Note: data from 2019 list. There's quite a few non-Europeans.
This is important because we want a per capita measure of sorts. For highly regarded journals, European built countries produced about 75% of science (Nature Index), but maybe 30% of top fraudsters.