1. Minnesota Transracial Adoption Study • Design: Black, biracial, and White infants adopted into White, middle-class families in Minnesota. • Findings: • As children, Black and biracial adoptees scored well above national Black averages — strong evidence of environmental uplift. • By adolescence, average scores diverged again: White adoptees ≈106, biracial ≈99, Black adoptees ≈89. • Critiques: • Equalizing family SES ≠ equalizing peer environment, discrimination, or racial identity stress. • Some adoptees were placed later or under selective conditions. • Attrition and different test batteries complicate comparisons. • Counters: • Even within the same families, mean differences persisted into adolescence, suggesting environment raises averages but doesn’t fully eliminate gaps in this design. • The pattern is consistent across multiple test batteries and waves. • Even environmental theorists acknowledge this is the hardest case for their position.
Citation: Scarr & Weinberg (1976, Intelligence); Weinberg, Scarr & Waldman (1992, Intelligence).
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2. Texas Adoption Project • Design: Hundreds of adoptees reared in middle-class homes; IQs of both biological and adoptive parents measured. • Findings: • Adoptees’ IQs resembled biological parents more than adoptive parents, showing strong heritability. • At the same time, adoption into advantaged homes raised average scores. • Critiques: • Sample was mostly White, so not directly a race-gap study. • Possible selective placement inflated genetic resemblance. • Counters: • Demonstrates the principle: environment lifts the whole distribution, but genetic differences remain visible within the same rearing context. • Longitudinal data show both genetic and environmental effects over time.
Citation: Horn, Loehlin & Willerman (1979, Behavior Genetics); Loehlin, Horn & Willerman (1989, Personality and Individual Differences).
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3. SES-Controlled Large-Scale Datasets • Design: National longitudinal samples (e.g., NLSY/AFQT, NAEP) where Black and White individuals are compared after matching or controlling for parental education, income, and related SES variables. • Findings: • Gaps shrink substantially but often do not vanish. Residuals of ~0.5 SD (7–10 IQ points) remain in some analyses. • Critiques: • SES controls are incomplete — they don’t capture school quality, wealth, neighborhood safety, health disparities, toxin exposure, or cumulative disadvantage. • Gaps have narrowed markedly over decades, inconsistent with a fixed genetic explanation. • Counters: • Residuals are real and cannot be dismissed; they represent variance unexplained by measured SES. • Long-term trend data (e.g., NAEP) show that policy, resources, and social changes can close much of the gap.
Citation: Herrnstein & Murray (1994, The Bell Curve); Neal (2006, Handbook of the Economics of Education); Reardon, Kalogrides & Shores (2019, American Journal of Sociology); NAEP Long-Term Trend Data.
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4. Smaller Adoption and Foster Care Studies • Design: Transracial adoption in Britain and Europe; biracial children reared in Japan. • Findings: • Minority adoptees gained substantially over national averages. • In some cases, their averages remained slightly below White adoptees in the same homes. • Critiques: • Small sample sizes, often nonrandom placements, and institutional rearing environments complicate conclusions. • Counters: • Consistency across multiple settings shows substantial environmental effects; where gaps persist, they tend to be smaller than national averages.
Citation: Tizard (1972, Race); Tizard & Phoenix (1974, New Society); Eyferth (1961, Archiv für die gesamte Psychologie); Nakao & Treas (1994, Social Science Research).
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The Bigger Picture • Persistent Gaps: Some adoption studies and large-scale SES-controlled datasets show that residual group differences remain even under attempts to equalize rearing conditions. • Critiques: These designs don’t fully equalize environment — schooling, peer context, health, and discrimination are all hard to control. • Counters: The fact that residuals persist shows we cannot dismiss genetic explanations entirely. At the same time, environmental levers (education, health, toxins, nutrition, early interventions) have been shown repeatedly to narrow or close most of the gap.
ChatGPT wrote this according to my specifications.
This is a utter lie: https://news.ycombinator.com/newsguidelines.html
If you're going to continue lying to my face, don't bother talking to me.
>If your uncertainty was whether we could set up dueling ChatGPT sessions: we very definitely can.
I posted sources here and had chatgpt summarize the sources simply because I don't have time to do a research session just for a thread like this. I'm sure you don't have time to do an actual research session either, so your welcome to do the same.
My opinions and analysis of the summaries are my own.
You also have the freedom to leave the conversation as well. Frankly your initial bullshit lie has left a bad taste in my mouth and I'm caring less and less about continueing this conversation.
https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
This would be the fault of the moderators for not directly putting it in the rules if that was the case.
Though I doubt they'd be ok with this entire thread as it's heated and the topic is flamewar-like even though I tried to direct it in a different direction initially. It already went off the rails with the other guy once he told me I was dumb and trying to establish race superiority among asians. Too late. I think I'll get warned or banned.
Anyway, I'm not disguising the content human generated. Additionally All I'm doing is asking the LLM to cite and summarize citations which you asked for. Manually finding those citations are tedious.
My opinions and thoughts are still human written and not AI generated.
What I find incredulous is that you have some problem with content that's AI generated even if it's actually true and even it's just flat summaries of citations. Like I told the LLM to find specific resources and summarize studies I have already seen so you don't have to go through the entire paper and you have a huge problem with that? Fine. You can just refuse to engage. Commenting on it is also "against the rules" per your link: https://news.ycombinator.com/item?id=44808351
I mean if you want you can flag my post and vote it down. I think it's extreme and an ass hole move so I don't do that to people I have different opinions with. It's up to you.
I literally said to you that chatGPT is JUST citations. My comments are my own, you can respond to my comments can you not? What if I used AI to spell check and repair grammar? End of the world and you can't respond? Are people so against AI that they lose all common sense?
>"Please don't post AI-generated comments, or any generated comments" seems pretty clear to me.
Did he say please don't post AI-generated citations? Is he referring to the entire post or all comments? Why not make it an official rule on the rules page. What does Dang say about this? Seems unclear. I think you're just being deliberate.
Bro. You don't need to respond if you don't want to. My citations are still there. You asked for it, you got it. You don't like it? I'm not going to manually do what chatgpt ALREADY did so conversation is over if you don't want to continue.
Good thing I used AI to assist me. I knew you'd leave. Mainly because there's really no solid evidence so a lot of this will go in circles. Good day sir.