> What do you think Murray's advocated policies entail?
He and Hernstein advocated for abandoning affirmative action, and divert funds away from supporting low IQ groups (e.g. welfare) into supporting high performance groups. This conclusion would always be debated among political lines as more left wing folks would argue against it in favor of accommodations, even in a world IQ was actual proven science.
> That group differences exist is an incontrovertible fact.
This is true, however the reason for this difference, and whether it is of societal significance, is up for debate.
I would argue that we should care more about SAT scores then IQ scores because SAT scores are actually used as an admission metric. These two correlate however I can just as well come up with a new metric which correlates with SAT and use that in my models in place of SAT, that doesn’t mean it is providing any additional info over SAT, nor that anyone should care about it.
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Or as M. C. Frey (2019) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6963451/ puts it:
> Finally, when we understand that the SAT is a reasonable measure of intelligence, we can use SAT scores as a proxy measure for time-consuming and sometimes unavailable traditional intelligence assessments, as dozens of researchers have been doing since 2004.
Although, I should say that Frey misses an important alternative interpretation of her conclusion here, which is to ask: “Why care about IQ if we can use SAT to measure the same thing?”
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We do care about the group difference present in SAT scores, and we do care that high/low SAT scores seem to follow generations. However we see that as something to rectify. Nutrition, childhood led exposure, high noise levels all contribute to lower SAT scores, so we try to eliminate those. We could do the same for IQ scores, but why would you? If we found out that 50% of the variance of SAT scores were explained by genetics, who cares? The effect size is still tiny compared to other reasons why people score low on these test. Lets fix those.
Lewontin's Fallacy is a silly path to go down. You can draw taxonomy lines wherever you want. If you base that on a silly metric you get a silly taxonomy. Junk-in Junk-out still applies even if you subscribe to Lewontin's Fallacy. This is especially true in the study of human behavior.
Humans are a remarkably homogeneous species, we share almost all the same genes. Our experience varies way more then our genes. And alas, that is how most people split us into behavioral groups, e.g. by education, by socio-economic class, by occupation, by geographic region, etc. Group difference down these groups is way more interesting study then down gene make-up. And alas, this is where you find most research which actually contributes to policy change and further our understanding of the human mind.
EDIT 2: If you want to see for your self how poor the scientific quality of The Bell Curve is, I recommend you read the sources it cites. Of particular interests is the meta-alalyses by R. Lynn (1991) [Here is a summary https://youtu.be/UBc7qBS1Ujo?t=4256].