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.
-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, 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 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.
[TODO: more examples of sex difference effect sizes, elaborate on "big" doesn't mean anything]
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_.
-Notably, Plomin and Turkheimer aren't actually disagreeing here: it's a difference in emphasis rather than facts. Polygenic scores _don't_ explain mechanisms—but might they end up being useful, and used, anyway? Murray's vision of social science is content to make predictions and "explain variance" while remaining ignorant of ultimate causality. Meanwhile, my cursory understanding (while kicking myself for [_still_](/2018/Dec/untitled-metablogging-26-december-2018/#daphne-koller-and-the-methods) not having put in the hours to get much farther into [_Probabilistic Graphical Models: Principles and Techniques_](https://mitpress.mit.edu/books/probabilistic-graphical-models)) was that you _need_ to understand causality in order to predict what interventions will have what effects: variance in rain may be statistically "explained by" variance in mud puddles, but you can't make it rain by turning the hose on. Maybe our feeble state of knowledge is _why_ we don't know how to find reliable large-effect environmental interventions that still yet might exist in the vastness of the space of possible interventions.
+Notably, Plomin and Turkheimer aren't actually disagreeing here: it's a difference in emphasis rather than facts. Polygenic scores _don't_ explain mechanisms—but might they end up being useful, and used, anyway? Murray's vision of social science is content to make predictions and "explain variance" while remaining ignorant of ultimate causality. Murray compares polygenic scores to "economic indexes predicting GDP growth", which is not necessarily a reassuring analogy to those who doubt how much of GDP represents real production rather than the "exhaust heat" of zero-sum contests in an environment of [manufactured scarcity](http://benjaminrosshoffman.com/there-is-a-war/) and [artificial demand](https://write.as/harold-lee/the-sliding-scale-of-bullshit-jobs).
-There are also some appendicies at the back of the book! Appendix 1 (reproduced from, um, one of Murray's earlier books with a coauthor) explains some basic statistics concepts. Appendix 2 ("Sexual Dimorphism in Humans") goes over the prevalence of intersex conditions and gays, and then—so much for this post broadening the [topic scope of this blog](/tag/two-type-taxonomy/)—transgender typology! Murray presents the Blanchard–Bailey–Lawrence–Littman view as fact, which I think is basically _correct_, but a more comprehensive treatment (which I concede may be too much too hope for from a mere Appendix) would have at least _mentioned_ alternative views ([Serano](https://rationalwiki.org/wiki/Intrinsic_Inclinations_Model)? [Veale](/papers/veale-lomax-clarke-identity_defense_model.pdf)?), if only to explain _why_ they're worth dismissing. (Contrast to the eight pages in the main text explaining why "But, but, epigenetics!" is worth dismissing.) Then Appendix 3 ("Sex Differences in Brain Volumes and Variance") has tables of brain-size data, and an explanation of the greater-male-variance hypothesis. Cool!
+Meanwhile, my cursory understanding (while kicking myself for [_still_](/2018/Dec/untitled-metablogging-26-december-2018/#daphne-koller-and-the-methods) not having put in the hours to get much farther into [_Probabilistic Graphical Models: Principles and Techniques_](https://mitpress.mit.edu/books/probabilistic-graphical-models)) was that you _need_ to understand causality in order to predict what interventions will have what effects: variance in rain may be statistically "explained by" variance in mud puddles, but you can't make it rain by turning the hose on. Maybe our feeble state of knowledge is _why_ we don't know how to find reliable large-effect environmental interventions that still yet might exist in the vastness of the space of possible interventions.
-[TODO: X chromosome greater male]
+There are also some appendicies at the back of the book! Appendix 1 (reproduced from, um, one of Murray's earlier books with a coauthor) explains some basic statistics concepts. Appendix 2 ("Sexual Dimorphism in Humans") goes over the prevalence of intersex conditions and gays, and then—so much for this post broadening the [topic scope of this blog](/tag/two-type-taxonomy/)—transgender typology! Murray presents the Blanchard–Bailey–Lawrence–Littman view as fact, which I think is basically _correct_, but a more comprehensive treatment (which I concede may be too much too hope for from a mere Appendix) would have at least _mentioned_ alternative views ([Serano](https://rationalwiki.org/wiki/Intrinsic_Inclinations_Model)? [Veale](/papers/veale-lomax-clarke-identity_defense_model.pdf)?), if only to explain _why_ they're worth dismissing. (Contrast to the eight pages in the main text explaining why "But, but, epigenetics!" is worth dismissing.) Then Appendix 3 ("Sex Differences in Brain Volumes and Variance") has tables of brain-size data, and an explanation of the greater-male-variance hypothesis. Cool!
-----
And that's where the blank slate doctrine absolutely _shines_—it's the [Schelling point](/2019/Oct/self-identity-is-a-schelling-point/#schelling-point) for preventing group conflicts! (A [_Schelling point_](https://www.lesswrong.com/posts/yJfBzcDL9fBHJfZ6P/nash-equilibria-and-schelling-points) is a choice that's salient as [a focus for mutual expectations](/2019/Dec/more-schelling/): what I think that you think that I think ... _&c._ we'll choose.) If you admit that there could differences between groups, you open up the questions of in what exact traits and of what exact magnitude, which people have an incentive to lie about to divert resources and power to their group by [establishing unfair conventions and then misrepresenting those contingent bargaining equilibria](/2020/Jan/book-review-the-origins-of-unfairness/) as some "inevitable" natural order.
-If you're afraid of purported answers being used as a pretext for oppression, you might hope to _make the question un-askable_. Can't oppress people on the basis of race if race _doesn't exist_! Denying the existence of sex is harder—which doesn't stop people from occasionally trying. But the taboo mostly only applies to _psychological_ trait differences, because those are more [politically sensitive](http://benjaminrosshoffman.com/judgment-punishment-and-the-information-suppression-field/)—and easier to motivatedly _see what you want to see_: whereas things like height or skin tone can be directly seen and uncontroversially measured with well-understood physical instruments (like a meterstick or digital photo pixel values), psychological assessments are _much_ more complicated and therefore hard to detach from the eye of the beholder. (If I describe Mary as "warm, compassionate, and agreeable", the words mean _something_ in the sense that they change what experiences you anticipate—if you believed my report, you would be _surprised_ if Mary were to kick your dog and make fun of your nose job—but the things that they mean are a high-level statistical signal in behavior for which we [don't have a simple measurement device](https://www.lesswrong.com/posts/edEXi4SpkXfvaX42j/schelling-categories-and-simple-membership-tests) like a meterstick to appeal to if you and I don't trust each other's character assessments of Mary.)
+If you're afraid of purported answers being used as a pretext for oppression, you might hope to _make the question un-askable_. Can't oppress people on the basis of race if race _doesn't exist_! Denying the existence of sex is harder—which doesn't stop people from occasionally trying. But the taboo mostly only applies to _psychological_ trait differences, because those are a [sensitive subject](http://benjaminrosshoffman.com/judgment-punishment-and-the-information-suppression-field/)—and easier to motivatedly _see what you want to see_: whereas things like height or skin tone can be directly seen and uncontroversially measured with well-understood physical instruments (like a meterstick or digital photo pixel values), psychological assessments are _much_ more complicated and therefore hard to detach from the eye of the beholder. (If I describe Mary as "warm, compassionate, and agreeable", the words mean _something_ in the sense that they change what experiences you anticipate—if you believed my report, you would be _surprised_ if Mary were to kick your dog and make fun of your nose job—but the things that they mean are a high-level statistical signal in behavior for which we [don't have a simple measurement device](https://www.lesswrong.com/posts/edEXi4SpkXfvaX42j/schelling-categories-and-simple-membership-tests) like a meterstick to appeal to if you and I don't trust each other's character assessments of Mary.)
Notice how the "not allowing sex and race differences in psychological traits to appear on shared maps is the Schelling point for resistance to sex- and race-based oppression" actually gives us an _explanation_ for _why_ one might reasonably have a sense that there are dread doors that we must not open. Undermining the "everyone is Actually Equal" Schelling point could [catalyze a preference cascade](https://www.reddit.com/r/slatestarcodex/comments/8q8p6n/culture_war_roundup_for_june_11/e0mxwe9/)—a [slide down the slippery slope to the the next Schelling point](https://www.lesswrong.com/posts/Kbm6QnJv9dgWsPHQP/schelling-fences-on-slippery-slopes), which might be a lot worse than the _status quo_ on the "amount of rape and genocide" metric, even if it does slightly better on "estimating heritability coefficients." The orthodoxy isn't just being dumb for no reason. In analogy, Galileo and Darwin weren't _trying_ to undermine Christianity—they had much more interesting things to think about—but religious authorities were _right_ to fear heliocentrism and evolution: if the prevailing coordination equilibrium depends on lies, then telling the truth _is_ a threat and it _is_ disloyal. And if the prevailing coordination equilibrium is basically _good_, then you can see why purported truth-tellers striking at the heart of the faith might be believed to be evil.
And sufficient suspicion makes communication nearly impossible. (If you _know_ someone is lying, their words mean nothing, [not even as the opposite of the truth](https://www.lesswrong.com/posts/qNZM3EGoE5ZeMdCRt/reversed-stupidity-is-not-intelligence).) As far as many of Murray's detractors are concerned, it almost doesn't matter what the text of _Human Diversity_ says, how meticulously researched of a psychology/neuroscience/genetics lit review it is. From their perspective, Murray is "hiding the ball": they're not mad about _this_ book; they're mad about specifically chapters 13 and 14 of a book Murray coauthored twenty-five years ago. (I don't think I'm claiming to be a mind-reader here; the first 20% of [_The New York Times_'s review of _Human Diversity_](https://archive.is/b4xKB) is pretty explicit and representative.)
-In 1994's _The Bell Curve: Intelligence and Class Structure in American Life_, Murray and coauthor Richard J. Herrnstein argued that a lot of variation in life outcomes is explained by variation in intelligence. Some people think that folk concepts of "intelligence" or being "smart" are ill-defined and therefore not a proper object of scientific study. But that hasn't stopped some psychologists from trying to construct tests purporting to measure an "intelligence quotient" (or _IQ_ for short). It turns out that if you give people a bunch of different mental tests, the results all positively correlate with each other: people who are good at one mental task, like listening to a list of numbers and repeating them backwards ("reverse digit span"), are also good at others, like knowing what words mean ("vocabulary"). There's a lot of fancy linear algebra involved, but basically, you can visualize people's test results as a hyperellipsoid in some high-dimensional space where the dimensions are the different tests. (I rely on this ["configuration space"](https://www.lesswrong.com/posts/WBw8dDkAWohFjWQSk/the-cluster-structure-of-thingspace) visual metaphor _so much_ for _so many_ things that when I started [my secret ("secret") gender blog](/), it felt right to put it under a `.space` [TLD](https://en.wikipedia.org/wiki/Top-level_domain).) The longest axis of the hyperellipsoid corresponds to the "_g_ factor" of "general" intelligence—the choice of axis that cuts through the most variance in mental abilities.
+In 1994's _The Bell Curve: Intelligence and Class Structure in American Life_, Murray and coauthor Richard J. Herrnstein argued that a lot of variation in life outcomes is explained by variation in intelligence. Some people think that folk concepts of "intelligence" or being "smart" are ill-defined and therefore not a proper object of scientific study. But that hasn't stopped some psychologists from trying to construct tests purporting to measure an "intelligence quotient" (or _IQ_ for short). It turns out that if you give people a bunch of different mental tests, the results all positively correlate with each other: people who are good at one mental task, like listening to a list of numbers and repeating them backwards ("reverse digit span"), are also good at others, like knowing what words mean ("vocabulary"). There's a lot of fancy linear algebra involved, but basically, you can visualize people's test results as a hyper[ellipsoid](https://en.wikipedia.org/wiki/Ellipsoid) in some high-dimensional space where the dimensions are the different tests. (I rely on this ["configuration space"](https://www.lesswrong.com/posts/WBw8dDkAWohFjWQSk/the-cluster-structure-of-thingspace) visual metaphor _so much_ for _so many_ things that when I started [my secret ("secret") gender blog](/), it felt right to put it under a `.space` [TLD](https://en.wikipedia.org/wiki/Top-level_domain).) The longest axis of the hyperellipsoid corresponds to the "_g_ factor" of "general" intelligence—the choice of axis that cuts through the most variance in mental abilities.
+
+It's important not to overinterpret the _g_ factor as some unitary essence of intelligence rather than the length of a hyperellipsoid. It seems likely that [if you gave people a bunch of _physical_ tests, they would positively correlate with each other](https://www.talyarkoni.org/blog/2010/03/07/what-the-general-factor-of-intelligence-is-and-isnt-or-why-intuitive-unitarianism-is-a-lousy-guide-to-the-neurobiology-of-higher-cognitive-ability/), such that you could extract a ["general factor of athleticism"](https://isteve.blogspot.com/2007/09/g-factor-of-sports.html). (It would be really interesting if anyone's actually done this using the same methodology used to construct IQ tests!) But _athleticism_ is going to be an _very_ "coarse" construct for which [the tails come apart](https://www.lesswrong.com/posts/dC7mP5nSwvpL65Qu5/why-the-tails-come-apart): for example, world champion 100-meter sprinter Usain Bolt's best time in the _800_ meters is [reportedly only around 2:10](https://www.newyorker.com/sports/sporting-scene/how-fast-would-usain-bolt-run-the-mile) [or 2:07](https://archive.is/T988h)! (For comparison, _I_ ran a 2:08.3 in high school once.)
-So Murray and Herrnstein talk about this "intelligence" thingy, and how it's heritable, and how it predicts income, school success, not being a criminal, _&c._, and how this has all sorts of implications for Society and inequality and class structure and stuff. [TODO: mention "Coming Apart" thesis?]
+Anyway, so Murray and Herrnstein talk about this "intelligence" construct, and how it's heritable, and how it predicts income, school success, not being a criminal, _&c._, and how this has all sorts of implications for Society and inequality and class structure and stuff. [TODO: mention "Coming Apart" thesis?]
This _should_ just be more social-science nerd stuff, the sort of thing that would only draw your attention if, like me, you feel bad about not being smart enough to do algebraic topology and want to console yourself by at least knowing about the Science of not being smart enough to do algebraic topology. The reason everyone _and her dog_ is still mad at Charles Murray a quarter of a century later is Chapter 13, "Ethnic Differences in Cognitive Ability", and Chapter 14, "Ethnic Inequalities in Relation to IQ". So, _apparently_, different ethnic/"racial" groups have different average scores on IQ tests. [Ashkenazi Jews do the best](https://slatestarcodex.com/2017/05/26/the-atomic-bomb-considered-as-hungarian-high-school-science-fair-project/), which is why I sometimes privately joke that the fact that I'm [only 85% Ashkenazi (according to 23andMe)](/images/ancestry_report.png) explains my low IQ. ([I got a 131](/images/wisc-iii_result.jpg) on the [WISC-III](https://en.wikipedia.org/wiki/Wechsler_Intelligence_Scale_for_Children) at age 10, but that's pretty dumb compared to some of my [robot-cult](/tag/my-robot-cult/) friends.) East Asians do a little better than Europeans/"whites". And—this is the part that no one is happy about—the difference between U.S. whites and U.S. blacks is about Cohen's _d_ ≈ 1. (If two groups differ by _d_ = 1 on some measurement that's normally distributed within each group, that means that the mean of the group with the lower average measurement is at the 16th percentile of the group with the higher average measurement, or that a uniformly-randomly selected member of the group with the higher average measurement has a probability of about 0.76 have having a higher measurement than a uniformly-randomly selected member of the group with the lower average measurement.)
I used to be a naïve egalitarian. I was very passionate about it. I was eighteen years old. I am—again—still fond of the moral sentiment, and eager to renormalize it into something that makes sense. (Some egalitarian anxieties do translate perfectly well into the Bayesian setting, as I'll explain in a moment.) But the abject horror I felt at eighteen at the mere suggestion of _making generalizations_ about _people_ just—doesn't make sense. Not that it _shouldn't_ be practiced (it's not that my heart wasn't in the right place), but that it _can't_ be practiced—that the people who think they're practicing it are just confused about how their own minds work.
-Give people photographs of various women and men and ask them to judge how tall the people in the photos are, as [Nelson _et al._ 1990 did](/papers/nelson_et_al-everyday_base_rates_sex_stereotypes_potent_and_resilient.pdf), and people's guesses reflect both the photo-subjects' actual heights, but also (to a lesser degree) their sex. Unless you expect people to be perfect at assessing height from photographs (when they don't know how far away the cameraperson was standing, aren't ["trigonometrically omniscient"](https://plato.stanford.edu/entries/logic-epistemic/#LogiOmni), _&c._), this behavior is just _correct_: men really are taller than women on average (I've seen _d_ ≈ 1.4–1.7 depending on the source), so P(true-height|apparent-height, sex) ≠ P(height|apparent-height) because of [regression to the mean](https://en.wikipedia.org/wiki/Regression_toward_the_mean) (and women and men regress to different means). But [this all happens subconsciously](TODO: "Peering Through Reverent Fingers"): in the same study, when the authors tried height-matching the photographs (for every photo of a woman of a given height, there was another photo in the set of a man of the same height) _and telling_ the participants about the height-matching _and_ offering a cash reward to the best height-judge, more than half of the stereotyping effect remained. It would seem that people can't consciously readjust their learned priors in reaction to verbal instructions pertaining to an artificial context.
-
-Once you understand at a _technical_ level that probabilistic reasoning about demographic features is both epistemically justified, _and_ implicitly implemented as part of the way your brain processes information _anyway_, then a moral theory that forbids this starts to look much less compelling. Maybe a Bayesian superintelligence could redesign the human brain to _not_ use Bayesian reasoning when contemporary egalitarians would find that ideologically disagreeable? But a world populated by such people, constitutionally incapable of reacting to statistical regularities that we, in our world, automatically take into account (without necessarily noticing that we do), would likely come off as creepy or uncanny.
-
-[TODO: elaborate on a specific uncanniness: maybe "Self-Made Man" and early-onset trans people?!]
-
-[TODO: really need to address "But choice!" or "But not for psychology!" objections]
-
-Of course, statistical discrimination on demographic features is only epistemically justified to exactly the extent that it helps _get the right answer_. Renormalized-egalitarians can still be unhappy about the monstrous tragedies where I have moral property P but I _can't prove it to you_, so you instead guess _incorrectly_ that I don't just because other people who look like me mostly don't, and you don't have any better information to go on. 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 also 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 racism. 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 can realistically only be solved with _better tests_ and _better signals_, not by _pretending not to have a prior_.
-
+Give people photographs of various women and men and ask them to judge how tall the people in the photos are, as [Nelson _et al._ 1990 did](/papers/nelson_et_al-everyday_base_rates_sex_stereotypes_potent_and_resilient.pdf), and people's guesses reflect both the photo-subjects' actual heights, but also (to a lesser degree) their sex. Unless you expect people to be perfect at assessing height from photographs (when they don't know how far away the cameraperson was standing, aren't ["trigonometrically omniscient"](https://plato.stanford.edu/entries/logic-epistemic/#LogiOmni), _&c._), this behavior is just _correct_: men really are taller than women on average (I've seen _d_ ≈ 1.4–1.7 depending on the source), so P(true-height|apparent-height, sex) ≠ P(height|apparent-height) because of [regression to the mean](https://en.wikipedia.org/wiki/Regression_toward_the_mean) (and women and men regress to different means). But [this all happens subconsciously](/2020/Apr/peering-through-reverent-fingers/): in the same study, when the authors tried height-matching the photographs (for every photo of a woman of a given height, there was another photo in the set of a man of the same height) _and telling_ the participants about the height-matching _and_ offering a cash reward to the best height-judge, more than half of the stereotyping effect remained. It would seem that people can't consciously readjust their learned priors in reaction to verbal instructions pertaining to an artificial context.
+Once you understand at a _technical_ level that probabilistic reasoning about demographic features is both epistemically justified, _and_ implicitly implemented as part of the way your brain processes information _anyway_, then a moral theory that forbids this starts to look less compelling? Of course, statistical discrimination on demographic features is only epistemically justified to exactly the extent that it helps _get the right answer_. Renormalized-egalitarians can still be properly outraged about the monstrous tragedies where I have moral property P but I _can't prove it to you_, so you instead guess _incorrectly_ that I don't just because other people who look like me mostly don't, and you don't have any better information to go on—or tragedies in which a feedback loop between predictions and social norms creates or amplifies group differences that wouldn't exist under some other social equilibrium.
+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_.
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—
I agree with Murray that this kind of psychology explains a lot of the resistance to hereditarian explanations. But as long as we're accusing people of motivated reasoning, I think Murray's solution is engaging in a similar kind of denial, but just putting it in a different place. The idea that people are unequal in ways that matter is [legitimately too horrifying to contemplate](https://www.lesswrong.com/posts/faHbrHuPziFH7Ef7p/why-are-individual-iq-differences-ok), so liberals [deny the inequality](/2017/Dec/theres-a-land-that-i-see-or-the-spirit-of-intervention/), and conservatives deny [that it matters](https://www.lesswrong.com/posts/NG4XQEL5PTyguDMff/but-it-doesn-t-matter).
-
https://www.lesswrong.com/posts/Aud7CL7uhz55KL8jG/transhumanism-as-simplified-humanism
Each of us in her own way.
- - I don't know how to build a better world, but my first step is to go a little meta and talk about why we can't talk, and take seriously the possible harms from talking, rather than just asserting that free speech and civil discourse is Actually Good the way
- * the likes of Cofnas/Winegard/Murray do (being a nobody blogger probably helps; I have an excuse)
+TODO—
+
+ * need to clearly define before casually using later: "cognitive repetioires", "egalitarian", "renormalized"
+ * "genders have been identified"
+
+"I realize I am writing in an LGBT era when some argue that 63 distinct genders have been identified," Murray writes at the beginning of Appendix 2. But I think this would fail to pass the [Ideological Turing Test](https://www.econlib.org/archives/2011/06/the_ideological.html).
+
+The language of _has been identified_
+
+
+
+As economist Glenn Loury points out in _The Anatomy of Racial Inequality_, cognitive abilities decline with age, and yet we don't see a moral panic about the consequences of an aging workforce, because older people are construed as an "us"—our mothers and fathers—rather than an outgroup.
+
- * women and courage
* Embryo selection looks _really important_; I don't want to give amunition to racists, but I need to talk about that—and the recent Dawkins brouhaha says we can't even talk about that; and the ways I'm worried about eugenics being misused aren't even on the radar
-* "genders have been identified"
-* Hyde/Fine binary notes: p. 388
-* need to talk about individual differences being non-threatening
-* need to clearly define before casually using later: "cognitive repetioires", "egalitarian", "renormalized"
+
+
+* stages of HBD
+
+ * I have an excuse; telling the truth is a Schelling point (https://www.lesswrong.com/posts/tCwresAuSvk867rzH/speaking-truth-to-power-is-a-schelling-point)
+
+
+------
+
+
* it's actually a _selective_ blank slate (Winegard: https://quillette.com/2019/03/09/progressivism-and-the-west/ )
-* work in "Can Race Be Erased" result
-* Glenn Loury on stigma (older people are also dumber, but that's not a political firebomb)
-* Usain Bolt and the general factor of athleticism: https://www.letsrun.com/forum/flat_read.php?thread=7703577 https://isteve.blogspot.com/2007/09/g-factor-of-sports.html (I ran a 2:08.3 when I was sixteen years old.); the tails come apart ; https://www.newyorker.com/sports/sporting-scene/how-fast-would-usain-bolt-run-the-mile
-* blank slate coordination hurt me personally; but just tell the damn truth is also a Schelling point ("Speaking Truth to Power is ...")
+ * women and courage
+* Hyde/Fine binary notes: p. 398
+* need to talk about individual differences being non-threatening
+
+
+
+
-"I realize I am writing in an LGBT era when some argue that 63 distinct genders have been identified," Murray writes at the beginning of Appendix 2. But this is failing to pass the [Ideological Turing Test](https://www.econlib.org/archives/2011/06/the_ideological.html).
-The language of _has been identified_
-* Murray says polygenic scores are like GDP ... I bet Ben and Michael would have something to say about that analogy!
> Stage-5 (Acceptance): "Blank slate liberalism really has been a mountain of dishonest garbage, hasn’t it? Guess it’s time for it to die ..."
+(Okay, I was brainwashed by progressivism pretty hard, but ideologies need to appeal to something in human nature; you can't brainwash a human with random bits; they need to be specific bits with something good in them.)
+
+
—and the people who claim not to have an agenda are lying. (The most I can credibly claim for myself is that I try to keep my agenda reasonably _minimalist_—and the reader must judge for herself to what extent I succeed.)
A Book Review
-Someone wrote a blog post reviewing a book by some sociologist named Murray. Never heard of him. Anyway, I couldn't get through the whole thing because the reviewer has this _really obnoxious_ writing style that uses way too many italics and exclamation points (as well as occasional weirdly out-of-place cuss words?!), but I did notice that he (?) links to _Less Wrong_ a few (or twenty) times, which is something I don't see "in the wild" very often these days, so I "thought it couldn't hurt" to share the link here in case one of you happens to find it interesting??
+(_Content warning_: [politics](https://www.lesswrong.com/posts/9weLK2AJ9JEt2Tt8f/politics-is-the-mind-killer). Read with caution, as always.)
+
+Someone wrote a blog post reviewing a book by some sociologist named Murray. Never heard of him. Anyway, I couldn't get through the whole thing because the reviewer has this _really obnoxious_ writing style that uses way too many italics and exclamation points (as well as occasional weirdly out-of-place cuss words?!), but I did notice that he (?) links to _Less Wrong_ a few times, which is something I don't see "in the wild" very often these days, so I "thought it couldn't hurt" to share the link here in case one of you happens to find it interesting??
------
projects / Ultimately_Untrue_Thought.git / commitdiff