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.
Looking at the broader construct of misconduct, we can do the same thing. It seems East Asians commit this about 40x times more than Europeans. Staggering.
Some clever researchers used scraping to download 1000s studies and looked for studies with duplicated images from other studies.
One journal editor went to the unusual step of analyzing the data in submitted papers. This is what he found:
Looking beyond science, to other life dishonesty, we may note that in Asia, they make heist-type movies where the object is test cheating. Here, Thailand.
There was the famous wallet study too.
Broader still, corruption index (note Singapore!)
We also studied dishonesty by race in survey data, by self-report, parent-report, and interviewer-report. Too few Asians unfortunately, but the other gaps were seen as expected.
You have maybe seen this plot. It shows ratings of races in USA by race. The key result is that each race favors their own, except for Whites who are apparently race-blind.
Since it only covered a single year, 2020, I wondered if this would replicate across years of data. So I downloaded the data for 1964-2024.
So we see that the result replicated (I didn't use survey weights). And indeed, in 2020 and 2024, Whites have about zero ethnocentrism.
But this pattern among Whites is more complex. Here are the ratings by political ideology (self-rated 1-7 scale). The below average attitude towards fellow Whites is concentrated on the left, just as @ZachG932 found before. Especially the far left.
Mental issues roughly follow a hierarchical pattern, like cognitive abilities, like a general factor on top. At least, statistically.
The motivating factors behind this approach compared to the categorical (diagnostic) approach are: 1) evidence of continuity between clusters, 2) binary encoding of continuous data loses information, 3) correlations among diagnoses are the norm, 4) a given person may not quality for any particular diagnosis, yet have severe symptoms.
Some aspects of mental problems haven't been integrated into the hierarchical model yet. Say, unusual sexual interests (from foot fetishes to pedophilia and rape fetishes).
US Naval Academy: "a white applicant with a 5% chance of admission would have a 50% chance if evaluated as Black, and more than 70% of Black admits would not have been admitted under a race-neutral system"
Whites the most systematically discriminated against race.
The usual SAT gaps among applicants.
US military looks like other publicly funded institutions. A jobs program for non-Whites.