Tags: Charles Murray, review (book), intelligence, race, sex differences, Emacs, politics, probability, topology, COVID-19
Status: draft
-[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 different from each other, including differences in _cognitive repertoires_ (author Charles Murray's choice of phrase for saving nine syllables contrasted to "personality, abilities, and social behavior"). In [my last book review](/2020/Jan/book-review-the-origins-of-unfairness/), I mentioned that I had been thinking about broadening the topic scope of this blog, and this book review seems like an okay place to start!
+[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 different from each other, including differences in _cognitive repertoires_ (Murray's choice of phrase for shaving nine syllables off "personality, abilities, and social behavior"). In [my last book review](/2020/Jan/book-review-the-origins-of-unfairness/), I mentioned that I had been thinking about broadening the topic scope of this blog, and this book review seems like an okay place to start!
Honestly, I feel like I already knew most of this stuff?—sex differences in particular are kind of _my bag_—but many 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 Jane 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".
-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, you should probably skip this post and [go buy the source material](https://www.amazon.com/dp/B07Y82KNS1/)—or maybe even a grown-up textbook!
+In the first part of this blog post, I'm going to summarize what I learned from (or thought about, 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, you should probably skip this post and [go buy the source material](https://www.amazon.com/dp/B07Y82KNS1/)—or maybe even a grown-up textbook!
The second part of this blog post is irrelevant.
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_—the difference between two groups' means in terms of their pooled standard deviation—lets us give a _quantitative_ answer to _how much_ men are taller than women: I've seen reports of _d_ ≈ 1.4–1.7 depending on the source, a lot smaller than the sex difference in murder rates (_d_ ≈ 2.5), but much bigger than the difference in verbal skills (_d_ ≈ 0.3, favoring women).
-If you have a quantitative effect size, then you can [visualize the overlapping distributions](https://rpsychologist.com/d3/cohend/), and the question of whether the reality of the data should be summarized in English as a "large difference" or a "small difference" becomes _much less interesting_, bordering on meaningless.
+Once you have a quantitative effect size, then you can [visualize the overlapping distributions](https://rpsychologist.com/d3/cohend/), and the question of whether the reality of the data should be summarized in English as a "large difference" or a "small difference" becomes _much less interesting_, bordering on meaningless.
-Murray also addresses the issue of aggregating effect sizes—something [I've been meaning to get around to blogging about](/2018/Dec/untitled-metablogging-26-december-2018/#high-dimensional-social-science-and-the-conjunction-of-small-effect-sizes) more exhaustively for a while in this context of group differences (although at least, um, my favorite author on _Less Wrong_ [covered it in the purely abstract setting](https://www.lesswrong.com/posts/cu7YY7WdgJBs3DpmJ/the-univariate-fallacy)): small effect sizes in any single measurement can amount to a _big_ difference when you're considering many measurements at once. That's how people can [distinguish female and male faces at 96% accuracy](http://unremediatedgender.space/papers/bruce_et_al-sex_discrimination_how_do_we_tell.pdf), even though there's no single measurement (like "eye width" or "nose height") offers that much predictive power.
+Murray also addresses the issue of aggregating effect sizes—something [I've been meaning to get around to blogging about](/2018/Dec/untitled-metablogging-26-december-2018/#high-dimensional-social-science-and-the-conjunction-of-small-effect-sizes) more exhaustively in this context of group differences (although at least, um, my favorite author on _Less Wrong_ [covered it in the purely abstract setting](https://www.lesswrong.com/posts/cu7YY7WdgJBs3DpmJ/the-univariate-fallacy)): small effect sizes in any single measurement (whatever "small" means) can amount to a _big_ difference when you're considering many measurements at once. That's how people can [distinguish female and male faces at 96% accuracy](http://unremediatedgender.space/papers/bruce_et_al-sex_discrimination_how_do_we_tell.pdf), even though there's no single measurement (like "eye width" or "nose height") offers that much predictive power.
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! They're also more into the Conventional, Artistic, and Social dimensions of the [Holland occupational-interests model](https://en.wikipedia.org/wiki/Holland_Codes).
You might think that this is all due to socialization, but then it's hard to explain why the same differences show up in different cultures—and why (counterintuitively) the differences seem _larger_ in richer, more feminist countries. (Although as evolutionary anthropologist [William Buckner](https://traditionsofconflict.com/) points out in [his](https://twitter.com/Evolving_Moloch/status/1228124441944584192) [social-media](https://twitter.com/Evolving_Moloch/status/1228860328483491840) [criticism](https://twitter.com/Evolving_Moloch/status/1228947493309698050) of _Human Diversity_, [W.E.I.R.D.](https://www.apa.org/monitor/2010/05/weird) samples from different countries aren't capturing the full range of human cultures.) You might think that the "larger differences in rich countries" result is an artifact: maybe people in less-feminist countries implicitly make within-sex comparisons when answering personality questions (_e.g._, "I'm competitive _for a woman_") whereas people in more-feminist countries use a less sexist standard of comparison, construing ratings as compared to people-in-general. Murray points out that this explanation still posits the existence of large sex differences in rich countries (while explaining away the unexpected cross-cultural difference-in-differences). Another possibility is that sexual dimorphism _in general_ increases with wealth, including, _e.g._, in height and blood pressure, not just in personality. (I notice that this is consilient with the view that [agriculture was a mistake](https://www.discovermagazine.com/planet-earth/the-worst-mistake-in-the-history-of-the-human-race) that suppresses humans' natural tendencies, and that people [revert to forager-like lifestyles](http://www.overcomingbias.com/2010/10/divide-forager-v-farmer.html) [in many ways](http://www.overcomingbias.com/2017/08/forager-v-farmer-elaborated.html) as the riches of the industrial revolution let them afford it.)
-Women are better at verbal ability and social cognition, whereas [men are better at visuospatial skills](http://zackmdavis.net/blog/2016/12/alpha-gamma-phi/). The sexes achieve similar levels of overall performance via somewhat different mental "toolkits." Murray devotes a section to a 2007 result of Johnson and Bouchard, who report that general intelligence ["masks the dimensions on which [sex differences in mental abilities] lie"](/papers/johnson-bouchard-sex_differences_in_mental_abilities_g_masks_the_dimensions.pdf): overall levels of mental well-functioning lead to underestimates of the effect sizes of specific mental abilities, which you want to statistically correct for. This result in particular is _super gratifying_ to me personally, because [I independently had a very similar idea a few months back](/2019/Sep/does-general-intelligence-deflate-standardized-effect-sizes-of-cognitive-sex-differences/)—it's _super validating_ as an amateur to find that the pros have been thinking along the same track!
+Women are better at verbal ability and social cognition, whereas [men are better at visuospatial skills](http://zackmdavis.net/blog/2016/12/alpha-gamma-phi/). The sexes achieve similar levels of overall performance via somewhat different mental "toolkits." Murray devotes a section to a 2007 result of Johnson and Bouchard, who report that general intelligence ["masks the dimensions on which [sex differences in mental abilities] lie"](/papers/johnson-bouchard-sex_differences_in_mental_abilities_g_masks_the_dimensions.pdf): people's overall skill in using tools from the metaphorical mental toolbox leads to underestimates of differences in toolkits (that is, nonmetaphorically, the effect sizes of sex differences in specific mental abilities), which you want to statistically correct for. This result in particular is _super gratifying_ to me personally, because [I independently had a very similar idea a few months back](/2019/Sep/does-general-intelligence-deflate-standardized-effect-sizes-of-cognitive-sex-differences/)—it's _super validating_ as an amateur to find that the pros have been thinking along the same track!
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".
The third part of the book is about genetic influences on class structure! Untangling the true causes of human variation is a really hard technical philosophy problem, but behavioral geneticists have at least gotten started with their simple _ACE_ model. It works like this: first, assume (that is, "pretend") that the genetic variation for a trait is _additive_ (if you have the appropriate SNP, you get more of the trait), rather than exhibiting _epistasis_ (where the effects of different loci interfere with each other) or Mendelian _dominance_ (where the presence of just one copy of an allele (of two) determines the phenotype, and it doesn't matter whether you heterozygously have a different allele as your second version of that gene). Then we pretend that we can partition the variance in phenotypes as the sum of the "additive" genetic variance _A_, plus the environmental variance "common" within a family _C_, plus "everything else" (including measurement "error" and the not-shared-within-families "environment") _E_. Briefly (albeit at the risk of being _cliché_): nature, nurture, and _noise_.
-Then we can estimate the sizes of the _A_, _C_, and _E_ components by studying fraternal and identical twins. (If you hear people talking about "twin studies", this is what they mean—_not_ case studies of identical twins raised apart, which _are_ really cool but don't happen very often.) Both kinds of twins have the same family environment _C_ at the same time (parents, socioeconomic status, schools, _&c._), but identical twins are twice as genetically related to each other as fraternal twins, so the extent to which the identical twins are more similar is going to pretty much be because of their genes. "Pretty much" in the sense that while there are ways in which the assumptions of the model aren't quite true (assortative mating makes fraternal twins more similar in the ways their parents were _already_ similar before mating, identical twins might get treated more similarly by "the environment" on account of their appearance), the _quantitative_ effect of these deviations are probably pretty small!
+Then we can estimate the sizes of the _A_, _C_, and _E_ components by studying fraternal and identical twins. (If you hear people talking about "twin studies", this is what they mean—_not_ case studies of identical twins raised apart, which _are_ really cool but don't happen very often.) Both kinds of twins have the same family environment _C_ at the same time (parents, socioeconomic status, schools, _&c._), but identical twins are twice as genetically related to each other as fraternal twins, so the extent to which the identical twins are more similar is going to pretty much be because of their genes. "Pretty much" in the sense that while there are ways in which the assumptions of the model aren't quite true (assortative mating makes fraternal twins more similar in the ways their parents were _already_ similar before mating, identical twins might get treated more similarly by "the environment" on account of their appearance), Murray assures us that the experts assure us that the _quantitative_ effect of these deviations are probably pretty small!
-Anyway, it turns out that the effect of the shared environment _C_ is way smaller than most people intuitively expect—next to zero for personality and adult intelligence. The environment matters—just not the part of the environment shared by sibling in the same family. Just not the part of the environment we know how to control. Thus, a lot of economic and class stratification actually ends up being along genetic lines: the nepotism of family wealth can buy opportunities and second chances, but it doesn't actually live your life for you.
+Anyway, it turns out that the effect of the shared environment _C_ for most outcomes is smaller than most people intuitively expect—actually close to zero for personality and adult intelligence specifically! Sometimes sloppy popularizers summarize this as "parenting doesn't matter" in full generality, but it depends on the trait or outcome you're measuring: for example, the shared environment component gets up to 25% for years-of-schooling ("educational attainment") and 36% for "basic interpersonal interactions." _Culture_ obviously exists, but for underlying psychological traits, the part of the environment that matters is mostly not shared by siblings in the same family—not the part of the environment we know how to control. Thus, a lot of economic and class stratification actually ends up being along genetic lines: the nepotism of family wealth can buy opportunities and second chances, but it doesn't actually live your life for you.
<a id="heritability-caveats"></a>It's important not to overinterpret the heritability results; there are a bunch of standard caveats that go here that everyone's treatment of the topic needs to include! Heritability is about the _variance_ in phenotypes that can be predicted by _variance_ in genes. This is _not_ the same concept as "controlled by genes." To see this, notice that the trait "number of heads" has a heritability of zero because the variance is zero: all living people have exactly one head. (Siamese twins are two people.) Heritability estimates are also necessarily bound to a particular population in a particular place and time, which can face constraints shaped solely by the environment. If you plant half of a batch of seeds in the shade and half in the sun, the variance in the heights of the resulting plants will be associated with variance in genes _within_ each group, but the difference _between_ the groups is solely determined by the sunniness of their environments. Likewise, in a Society with a cruel caste system under which children with red hair are denied internet access, part of the heritability of intellectual achievement is going to come from alleles that code for red hair. Even though (_ex hypothesi_) redheads have the same inherent intellectual potential as everyone else, the heritability computation can't see into worlds that are not our own, which might have vastly different gene–environment correlations.
+(I speculate that heritability calculations being so Society-bound might help make sense of the "small role of the shared environment" results that many still balk at. If the population you're studying goes to public schools—or schools at all, as contrasted to [other ways of living and learning](https://en.wikipedia.org/wiki/Unschooling)—that could suppress a lot of the variance that might otherwise occur in families.)
+
Old-timey geneticists used to think that they would find small number of "genes for" something, but it turns out that we live in an omnigenetic, pleiotropic world where lots and lots of SNPs each exert a tiny effect on potentially lots and lots of things. I feel like this probably _shouldn't_ have been surprising (genes code for amino-acid sequences, variation in what proteins get made from those amino-acid sequences is going to affect high-level behaviors, but high-level behaviors involve _lots_ of proteins in a super-complicated unpredictable way), but I guess it was.
Murray's penultimate chapter summarizes the state of a debate between a "Robert Plomin school" and an "Eric Turkheimer school" on the impact and import of polygenic scores, where we tally up all the SNPs someone has that are associated with a trait of interest.
-The starry-eyed view epitomized by Plomin says that polygenic scores are _super great_ and everyone _and [her](/2020/Apr/the-reverse-murray-rule/) dog_ should be excited about them: they're causal in only one direction (the trait can't cause the score) and they let us assess risks in individuals before they happen. Clinical psychology will enter a new era of "positive genomics", where we understand how to work with the underlying dimensions along which people vary (including positively), rather than focusing on treated "diagnoses" that people allegedly "have".
+The starry-eyed view epitomized by Plomin says that polygenic scores are _super great_ and everyone _and [her](/2020/Apr/the-reverse-murray-rule/) dog_ should be excited about them: they're causal in only one direction (the trait can't cause the score) and they let us assess risks in individuals before they happen. Clinical psychology will enter a new era of "positive genomics", where we understand how to work with the underlying dimensions along which people vary (including positively), rather than focusing on treating "diagnoses" that people allegedly "have".
The curmudgeonly view epitomized by Turkheimer says that Science is about understanding the _causal structure_ of phenomena, and that polygenic scores don't fucking tell us anything. [Marital status is heritable _in the same way_ that intelligence is heritable](http://www.geneticshumanagency.org/gha/the-ubiquity-problem-for-group-differences-in-behavior/), not because there are "divorce genes" in any meaningful biological sense, but because of a "universal, nonspecific genetic pull on everything": on average, people with more similar genes will make more similar proteins from those similar genes, and therefore end up with more similar phenotypes that interact with the environment in a more similar way, and _eventually_ (the causality flowing "upwards" through many hierarchical levels of organization) this shows up in the divorce statistics of a particular Society in a particular place and time. But this is opaque and banal; the real work of Science is in figuring out what all the particular gene variations actually _do_.
Nelson _et al._ also found that when the people in the photographs were pictured sitting down, then judgements of height depended much more on sex than when the photo-subjects were standing. This too makes Bayesian sense: if it's harder to tell how tall an individual is when they're sitting down, you rely more on your demographic prior. In order to reduce injustice to people who are an outlier for their group, one could argue that there's a moral imperative to seek out interventions to get more fine-grained information about individuals, so that we don't need to rely on the coarse, vague information embodied in demographic stereotypes. The _moral spirit_ of egalitarian–individualism mostly survives in our efforts to [hug the query](https://www.lesswrong.com/posts/2jp98zdLo898qExrr/hug-the-query) and get [specific information](/2017/Nov/interlude-x/) with which to discriminate amongst individuals. (And _discriminate_—[to distinguish, to make distinctions](https://en.wiktionary.org/wiki/discriminate)—is the correct word.) If you care about someone's height, it is _better_ to precisely measure it using a meterstick than to just look at them standing up, and it is better to look at them standing up than to look at them sitting down. If you care about someone's skills as potential employee, it is _better_ to give them a work-sample test that assesses the specific skills that you're interested in, than it is to rely on a general IQ test, and it's _far_ better to use an IQ test than to use mere stereotypes. If our means of measuring individuals aren't reliable or cheap enough, such that we still end up using prior information from immutable demographic categories, that's a problem of grave moral seriousness—but in light of the [_mathematical laws_](https://www.lesswrong.com/posts/eY45uCCX7DdwJ4Jha/no-one-can-exempt-you-from-rationality-s-laws) governing reasoning under uncertainty, it's a problem that realistically needs to be solved with _better tests_ and _better signals_, not by _pretending not to have a prior_. This could take the form of _finer-grained_ stereotypes. If someone says of me, "Taylor Saotome-Westlake? Oh, he's a _man_, you know what _they're_ like," I would be offended—I mean, I would if I still believed that getting offended ever helps with anything. (It _never helps_.) I'm _not_ like typical men, I _don't like_ typical men, and I don't want to be confused with them. But if someone says, "Taylor Saotome-Westlake? Oh, he's one of those IQ 130, [mid-to-low Conscientiousness and Agreeableness, high Openness](https://en.wikipedia.org/wiki/Big_Five_personality_traits), left-libertarian American Jewish atheist autogynephilic male computer programmers; you know what _they're_ like," my response is to nod and say, "Yeah, pretty much." I'm not _exactly_ like the others, but I don't mind being confused with them.
-The other place where I think Murray is hiding the ball (even from himself) is in his discussion of the value of cognitive abilities. Murray writes—
+The other place where I think Murray is hiding the ball (even from himself) is in the section on "reconstructing a moral vocabulary for discussing human differences." (I agree that this is a very important project!) Murray writes—
> I think at the root [of the reluctance to discuss immutable human differences] is the new upper class's conflation of intellectual ability and the professions it enables with human worth. Few admit it, of course. But the evolving zeitgeist of the new upper class has led to a misbegotten hierarchy whereby being a surgeon is _better_ in some sense of human worth than being an insurance salesman, being an executive in a high-tech firm is _better_ than being a housewife, and a neighborhood of people with advanced degrees is _better_ than a neighborhood of high-school graduates. To put it so baldly makes it obvious how senseless it is. There shouldn't be any relationship between these things and human worth.
projects / Ultimately_Untrue_Thought.git / blobdiff