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Konkvistador comments on LW Women- Minimizing the Inferential Distance - Less Wrong
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Until the child tells you their gender identity, don't assume it matches their body, and even after then don't police it. Any sentence that begins with a paraphrase of "girls do" (talk politely, their homework,...) or "girls don't" (wear spiderman suits, climb trees,...) is nearly certainly sexist, wrong, and harmful. Learn the standard ways that parents treat children differently by gender (assuming girls are upset where they'd assume boys are angry, for example) and proactively refuse to do, or permit them done by other adults.
I generally try to use probability when interacting with people. I know they are not as likely to jump of a bridge as to cross it. Amazingly it seems to help me have good relations with them. Incredible I know. I hear statistical reasoning about humans is evil though so maybe I shouldn't be sharing this advice.
I never did get why that is though.
In certain cases, it's evil (i.e. there should be an ethical injunction against it) because, due to corrupted mindware, certain people tend to overdo it (e.g., if they know that black people have a lower average IQ than white people, they'll consider a black person significantly stupider than a white person in the same situation even though the evidence race provides about intelligence is likely almost completely screened off by information about what they say, wear, and do).
That's not even the worst possibility-- a racist may resent black people who are smarter than they "ought" to be.
One might argue that that's not even a version of “statistical reasoning” corrupted by cognitive biases, that's just being an asshole.
One might, but it's plausible that being an asshole and having thinking that's corrupted by emotional habits are entangled.
I'd say “It's complicated.” Sometimes making someone less biased will make them more of a asshole.
BTW, I'm curious how Cognitive Reflection Test scores correlate with Big Five personality traits. I'd guess cbfvgvir pbeeryngvba jvgu Bcraarff naq Pbafpvragvbhfarff naq artngvir pbeeryngvba jvgu Arhebgvpvfz, ohg V unir ab vqrn nobhg Rkgebirefvba naq Nterrnoyrarff.
"Being an asshole" is a description of effects, not causes. In this case, the person's assholy behavior might result from being insecure and angry, scapegoating other races for their insecurity and anger, having false beliefs about them, and responding to confusion with denial rather than doubt.
Are the specific examples that JulianMorrison gave things that are statistically true about girls versus boys. Is it statistically true that girls don't climb trees? (I'm a girl, and tree climbing is awesome!)
Also, there's a difference between what you're talking about (using probability to predict behaviour when you know nothing else about others) and ways to raise children, since parents in part determine the future behaviour of their children. Even if it is statistically true, right now, that girls don't wear Spider-Man suits as often as boys, and get upset rather than angry, I don't think those states are the ideal world states. Treating your children like these stereotypes are true might be a self fulfilling prophecy.
Note that there are some examples that I think would be true. I do think that, on average, girls are more likely to get upset than angry when in a situation of conflict. But not always: I get upset more often, my brother gets angry, my sister gets angry, my dad gets upset. I do think that the average boy, if given a Barbie, is more likely to re-enact battles with it than dress it. But that doesn't mean it's a good parenting strategy to yell at your son because he's an outlier who likes to dress Barbies. (From a purely predictive view, you could probably make a boy happier by giving him something other than a Barbie for his birthday, but that's if you're not the parent and your actions aren't influencing his future preferences.)
This is what I was criticizing:
I also disagree with the first paragraph. If I have a daughter someday, I'm not going to treat her as gender-neutral-it's too much work and probably wouldn't work. I guess I just think that the examples in the second group aren't "gender identity" examples. At most they're gender stereotypes. I will treat my daughter as a girl, unless she tells me not to, but I'll happily climb trees with her, I wouldn't tell her to be polite because "girls are polite" (boys should be too!) and I won't encourage or expect her to be upset rather than angry.
What's your distinction between upset and angry?
When in a situation of conflict: Upset: assume you're the one in the wrong, blame yourself, not try to defend yourself, cry. (Or some but not all of these elements.) Angry: Assume you're right, blame the other person, argue back, yell. Or some but not all of these elements.
Obviously it depends on context. Some people have a very strong tendency to get upset, whereas others will sometimes be upset and sometimes be angry. I'm pretty strongly skewed towards getting upset; I don't like the experience of anger; but in a conflict with family members, I will frequently behave more angrily than upset.
BTW, by "assuming girls are upset where they'd assume boys are angry" I am referring to unconscious fact judgements about infants too young to verbalize the problem. (Cite: "pink brain blue brain" by Lise Eliot). Macho emotions are attributed to babies in who appear male and gentle ones to babies who appear female. Since baby sex is almost unmarked, that means going by the colour of the clothes. (And google "baby Storm" for an example of adults panicking and pillorying the parents if the cues that allow them to gender the baby are intentionally witheld.)
Ohh. Oops. Not how I interpreted it. Your original meaning is much less likely to be a true-ish stereotype than my interpretation.
Apply Bayes to making decisions in real life, in ways that the cool people don't? That idea will never fly on LessWrong!
There's not as much reason to pay attention to statistical reasoning when we have insight into causal mechanisms. Particularly when our knowledge of the causal mechanisms suggests that the statistical results are very susceptible to misleading interpretations.
Incidentally we have essentially perfect insight into the causal mechanisms of what makes a number prime, and yet this sort of reasoning is spectacularly successful: