1 Title: Book Review: Charles Murray's <em>Human Diversity: The Biology of Gender, Race, and Class</em>
4 Tags: review (book), race, sex differences
7 [This is a pretty good book](https://www.twelvebooks.com/titles/charles-murray/human-diversity/9781538744000/) about things we know about some ways in which people are taxonically different from each other! Honestly, I feel like I already knew most of this stuff?—sex differences in particular are kind of _my bag_—but some of the details were new to me, and it's nice to have it all bundled together in a paper book with lots of citations that I can chase down later when I'm skeptical or want more details about a specific thing! The main text is littered with pleonastic constructions like "The first author was Thisand-Such" (when discussing the results of a multi-author paper) or "Details are given in the note<sup>[n]</sup>", which feel clunky to read, but are _so much better_ than the all-too-common alternative of authors _not_ "showing their work".
9 In the first part of this blog post, I'm going to summarize what I learned from (or was reminded of by) _Human Diversity_, but it would be kind of unhealthy for you to rely too much on tertiary blog-post summaries of secondary semi-grown-up-book literature summaries, so if these topics happen to strike your scientific curiosity, maybe you should skip this post and [go buy the source material](https://www.amazon.com/dp/B07Y82KNS1/)—or maybe even a grown-up textbook!
11 The second part of this blog post is irrelevant.
15 _Human Diversity_ is divided into three parts corresponding to the topics in the subtitle! (Plus another part if you want some wrapping-up commentary from Murray.) So the first part is about things we know about some ways in which female people and male people are different from each other!
17 The first (short) chapter is mostly about explaining [Cohen's _d_](https://en.wikiversity.org/wiki/Cohen%27s_d) [effect sizes](https://en.wikipedia.org/wiki/Effect_size), which I think are solving a very important problem! When people say "Men are taller than women" you know they don't mean _all_ men are taller than _all_ women (because you know that they know that that's obviously not true), but that just raises the question of what they _do_ mean. Saying they mean it "generally", "on average", or "statistically" doesn't really solve the problem, because that covers everything between-but-not-including "No difference" to "Yes, literally all women and all men". Cohen's _d_ is the summary statistic that lets us _quantify_ statistical differences in standardized form: once you can [visualize the overlapping distributions](https://rpsychologist.com/d3/cohend/), whether the reality of the data should be summarized in English words as a "large difference" or a "small difference" becomes a _much less interesting_ question.
19 [multivariate effect sizes and the Marco del Guidice fan club, https://www.lesswrong.com/posts/cu7YY7WdgJBs3DpmJ/the-univariate-fallacy ]
21 Subsequent chapers address sex differences in personality, cognition, interests, and the brain. It turns out that women are more warm, empathetic, æsthetically discerning, and cooperative than men are! You might think that this is due to socialization, but then it's hard to explain why the same differences show up in different countries—and why the differences are seem _larger_ in richer, more feminist countries.
23 [TODO: differences in perception, or just more sexual dimorphism in general?]
25 Women are better at verbal ability and social cognition, whereas men are better at visuospatial skills.
27 Murray devotes a section discussing [dimensions which they lie]
29 The second part of the book is about some ways in which people with different ancestries are different from each other! Obviously, there are no "distinct" "races" (that would be dumb), but it turns out (as found by endeavors such as [Li _et al._ 2008](/papers/li_et_al-worldwide_human_relationships_inferred.pdf)) that when you throw clustering and [dimensionality-reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) algorithms at SNP data (<em>s</em>ingle <em>n</em>ucleotide <em>p</em>olymorphisms, places in the genome where more than one allele has non-negligible frequency), you get groupings that are a pretty good match to classical or self-identified "races".
31 Ask the computer to assume that an individual's ancestry came from _K_ fictive ancestral populations where _K_ := 2, and it'll infer that sub-Saharan Africans are descended entirely from one, East Asians and some native Americans are descended entirely from the other, and everyone else is an admixture. But if you set _K_ := 3, populations from Europe and the near East (which were construed as admixtures in the _K_ := 2 model) split off as a new "pure" cluster. And so on.
33 These ancestry groupings _are_ a "construct" in the sense that the groupings aren't "ordained by God"—the algorithm can find _K_ groupings for your choice of _K_—but _where_ it [draws those category boundaries](https://www.lesswrong.com/posts/esRZaPXSHgWzyB2NL/where-to-draw-the-boundaries) is a function of the data. The construct is doing _cognitive work_, concisely summarizing statistical regularities in the dataset (which is _too large_ for humans to hold in their heads all at once): a map that reflects a territory.
35 Twentieth-century theorists like Fisher and Haldane and whatshisface-the-guinea-pig-guy had already figured out a lot about how evolution works (stuff like, a mutation that confers a fitness advantage of _s_ has a probability of about 2<em>s</em> of sweeping to fixation), but a lot of hypotheses about recent human evolution weren't easy to test, or formulate, until the genome was sequenced!
37 our migration out of Africa
39 Humans interbred with Neanderthals and Denisovans
46 ... and that's the review that I
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