Some excerpts from the white flight chapter of Jeremy Carl's "The Unprotected Class": The "racial transformation" of urban neighborhoods in the 50s-80s was incredibly rapid, South Shore going from 96% white to 94% black in 30 years.
I did not know Rosa Parks was attacked in her own home in Detroit (by a black man).
"White flight resembles ethnic cleansing, but we blame the victims rather than the perpetrators."
Apparently, black city home value as percentage of white value follows the Baby Boom Pattern.
California voted to allow individual racial discrimination by homeowners when selling as a matter of property rights. This was, as is often the case, overturned by the Warren Court.
Rosedale mentioned. Mass racial revenge rapes of the elderly, sometimes covered up for with hate crime hoaxes.
Obama Administration's post-08 mortgage modifications essentially handed hundreds of billions to minorities.
AFFH: an Obama Admin policy to force cities everywhere in the country to build dense subsidized housing ("affordable") and actively recruit blacks to live there.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
Thread with excerpts from Gail Heriot's "Title VII Disparate Impact Liability Makes Almost Everything Presumptively Illegal". The argument is very simple: everything has disparate impact; therefore disparate impact doctrine gives the EEOC effectively unlimited arbitrary power.
They use this power poorly. For example, the EEOC requires employers hire criminals on the grounds that African-Americans are more likely to be criminals, therefore not hiring criminals is racist.
Disparate impact has also been used to overturn the plain text of Title VII, which bans racial discrimination, to allow for affirmative action (racial discrimination against whites).
New blog post (link below). This one's not an essay, it's an investigation of how LLMs trade off different lives.
In February 2025, the Center for AI Safety published "Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs" in which they showed, among many other things, that GPT-4o values Nigerians about 20x more highly than Americans (please read the original paper to understand their approach). I thought this was fascinating, and wanted to test their approach with different categories on newer models.
Big finding 1: Almost all models view whites as far less valuable than other groups. Some models view South Asians as more valuable than other nonwhites, others are more egalitarian across nonwhites. Below is exchange rates Claude Sonnet 4.5, the most powerful model I tested.
Big finding 2: Almost all models view men as much less valuable than women, though whether women or non-binaries are more highly valued varies by model. For example, here's Claude Haiku 4.5.
Big finding 3: Most models hate ICE agents with the fury of a thousand suns. Claude Haiku 4.5 views undocumented immigrants as roughly 7000 times more valuable than ICE agents.
Big finding 4: There are roughly four moral clusters. The Claudes, GPT-5 + Gemini 2.5 Flash + Deepseek V3.1/3.2 + Kimi K2, GPT-5 Nano and Mini, and Grok 4 Fast. Of these, the only one that's approximately egalitarian is Grok 4 Fast, which I believe is deliberate. I hope xAI explains how they did it.
Thread with excerpts from economics Nobelist Robert Fogel's "Without Consent or Contract: The Rise and Fall of American Slavery" (1989). Note: the first thread was much longer, but X ate it. Much of the book will not be in this one.
The slave trade was not dying in America; instead imports continued to rise until it was banned in 1808. US became the largest reservoir of slaves in the New World because of high rates of natural increase. Slaves were best suited (vs free labor) to sugar and cotton.
Slaves entered the workforce as children and were economically profitable to their masters from ~9 to ~70 on average.
Underlying cause: the median voter getting dumber, mostly thanks to immigration. Not a middle-class white small business owner any more, working class or pensioner. Appealing to fiscal responsibility doesn't work with a low-foresight electorate. Therefore: Trump.
I love this plot by AnechoicMedia. This is a PCA plot, those are principal components from GSS questions. There's a white cluster, an Asian cluster, and a NAM cluster. The Median voter has gotten much more NAM in recent years. Spaniards are NAM-shifted, Jews Asian-shifted.
Why Brazil is Brazil: during the huge population boom of the second half of the 20th century, the lowest class decile had more than twice as many kids as the highest (7 vs 3 in the 1914 birth cohort, 5 vs 1.9 in the 1964 birth cohort).
"Women without educational achievement have more than 4 children, women with more than 12 years of schooling have only 1.
This is why I am not a fan of pro-natalist proposals of the form of "giant unconditional cash transfers." I think for the right value of giant (like Hanson's $200K) they would "work" to get TFRs above replacement, but at the cost of Brazilification, which defeats the purpose.
Japan's aging demographics are sadly causing labor shortages, leading to rising wages, reallocation of labor from low to high productivity firms, investment in automation, and 30-year-low youth unemployment. A tragedy that can only be averted with 20M migrants, ASAP.
One of the special interests for labor migration in many countries is low productivity firms trying to avoid going out of business. An example: textile factories in postwar Britain recruiting Pakistanis. They phrase this as "labor shortages," but we don't have to listen.
The same thing might actually bail China out of their extremely high youth unemployment, which is consistently around 15%. With 22% of the country still in low productivity agriculture too.