The [COVID-19](https://en.wikipedia.org/wiki/Coronavirus_disease_2019) news is playing hell with my neuroticism. [They say](https://virologydownunder.com/past-time-to-tell-the-public-it-will-probably-go-pandemic-and-we-should-all-prepare-now/) you should stock up on needed prescription drugs, in case of supply-chain disruptions. I guess I'm glad that, unlike some of my friends who I am otherwise jealous of, I'm not dependent on drugs for the hormones that my body needs in order for my bones to not rot. I wish I had _known_ tweleve years ago, that accepting that dependency in exchange for its scintillating benefits was an _option_ for cases like mine. There's at least a consistency in this: it's _not safe_ to depend on the supply lines of a system that didn't have the all-around competency to [just tell me](/2016/Oct/exactly-what-it-says-on-the-tin/).
-Anyway, _besides_ the [Total Culture War over the future of my neurotype](/2020/Feb/if-in-some-smothering-dreams-you-too-could-pace/) tearing apart ten-year friendships and having me plotting to flee my hometown, my life is going pretty okay. I'm getting paid lots of money to sell insurance in Canada, and I have lots of things to look forward to, like the conclusion to the _Tangled_ sequel series, or the conclusion to the _Obnoxious Bad Decision Child_ sequel miniseries, or finishing my forthcoming review of the new Charles Murray book. (It's going to be great—a strategic bid to broaden the topic scope of the blog to "things that only right-wing Bad Guys want to talk about, but without myself being a right-wing Bad Guy" in _full generality_, not just for autogynephila and the [correspondence of language to reality](https://en.wikipedia.org/wiki/Rectification_of_names).)
+Anyway, _besides_ the [Total Culture War over the future of my neurotype](/2020/Feb/if-in-some-smothering-dreams-you-too-could-pace/) tearing apart ten-year friendships and having me plotting to flee my hometown, my life is going pretty okay. I'm getting paid lots of money to sell insurance in Canada, and I have lots of things to look forward to, like the conclusion to the _Tangled_ sequel series, or the conclusion to the _Obnoxious Bad Decision Child_ sequel miniseries, or finishing my forthcoming review of the new Charles Murray book. (It's going to be great—a bid to broaden the topic scope of the blog to "things that only right-wing Bad Guys want to talk about, but without myself being a right-wing Bad Guy" in _full generality_, not just for autogynephila and the [correspondence of language to reality](https://en.wikipedia.org/wiki/Rectification_of_names).)
Basically, _I want to live_. I know that now. And it's hard to shake the feeling that the forces trying to cloud my vision don't want me to.
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. [Divorce 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."
-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 [_Daphne Koller and the Methods of Rationality_](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—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. 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—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.
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!
It's important not to overinterpret the IQ-scores-by-race results; there are a bunch of standard caveats that go here that everyone's treatment of the topic needs to include. Again, just because variance in a trait is statistically associated with variance in genes _within_ a population, does _not_ mean that differences in that trait _between_ populations are _caused_ by genes: [remember the illustrations about](#heritability-caveats) sun-deprived plants and internet-deprived red-haired children. Group differences in observed tested IQs are entirely compatible with the blank slate doctrine, a world in which those differences are entirely due to the environment imposed by an overtly or structurally racist society. Maybe the tests are culturally biased. Maybe people with higher socioeconomic status get more opportunities to develop their intellect, and racism impedes socio-economic mobility. And so on.
-The problem is, a lot of the blank-slate-compatible hypotheses for group IQ differences become less compelling when you look into the details. "Maybe the tests are biased", for example, isn't an insurmountable defeater to the entire endeavor of psychometrics—it's _itself_ a testable hypothesis, or can become one if you specify what you mean by "bias" in detail. If a test question were biased against a group, you would expect
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+The problem is, a lot of the blank-slate-compatible hypotheses for group IQ differences become less compelling when you look into the details. "Maybe the tests are biased", for example, isn't an insurmountable defeater to the entire endeavor of psychometrics—it is _itself_ a falsifiable hypothesis, or can become one if you specify what you mean by "bias" in detail. If a test question were biased against a group, you would expect
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And, again, socio-psychological facts like character assessments are precisely those for which we have the _most_ reason to distrust each other's judgement: if I like Mary, I might say favorable but false things about her even if I would never tell a lie about homotopy groups. In the absence of a objectively calibrated compassion-o-meter, psychological scientists who want to study individual differences in compassion are mostly limited to doing statistics on people's verbal self-reports and other-reports—but if you don't trust what people _say_, it's at least not _obvious_ whether or how much more you should trust statistical analyses of what people say, in accordance with the ancient dictum: ["garbage in, garbage out."](https://en.wikipedia.org/wiki/Garbage_in,_garbage_out) Probably the neuroscientists are working on the compassion-o-meter, but they too face the problem of ensuring that their interpretations of their brain scans actually mean what they say they mean.
+
+Jensen—
+> the test must measure, in addition to the construct it purports to measure,
+some other characteristic or factor that is completely uncorrelated with the construct and on which the major group, on the average, exceeds the minor group A typical example is the case in which the major and minor groups differ in their native language. A person’s native language is presumably not correlated with the construct of intelligence. If the test involves the native language of the major group exclusively and the minor group has a different language, the test will most likely be positively biased in favor of the major group. In other words, the test is measuring something (in this case a specific language) in addition to the construct that it purports to measure, which condition favors the major group
+
+https://en.wikipedia.org/wiki/Black_Intelligence_Test_of_Cultural_Homogeneity
+
+Draw-a-Horse Pueblo
+
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This was the linkpost description text I initially drafted, before deciding that the "Straussian coyness" I [occasionally]() [succumb]() to is ultimately unbecoming.
projects / Ultimately_Untrue_Thought.git / commitdiff