Kaj_Sotala comments on Problems in evolutionary psychology - Less Wrong
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I should have made it more clear in the post that the primary target of the post was not professional, academic evolutionary psychology. Rather, I was primarily cautioning amateurs (such as LW regulars) about some of the caveats involved in evpsych and noting the rigor required for good theories. While the post does also serve as a warning to be cautious about sloppy research (or sloppy science journalism) that doesn't seem to be taking these issues into account, I don't question the claim that the people doing serious evpsych are aware of all the issues I mentioned, and are probably taking them into account.
My wording was probably a bit too strong. Anyway, I'll try to look up some examples once I wake up.
Huh. This is an excellent point; I'm now updating in favor of an increased probability for mental sex differences.
I was thinking of a study mentioned in one of Buss' textbooks, which I unfortunately don't have at hand right now. I will look up the exact citation.
Right. I should have been clearer on this, too. I did not mean to argue that the variation would disprove an evolutionary or biological basis for these traits. Instead, I was using it as a caution against making too many assumptions of specific individuals.
It may have been a bit misplaced in this post, as it's more of a general caveat about psychological research than a criticism of evpsych in particular: not many results in psychology are truly universal in that you couldn't find individuals who were counterexamples. I should possibly remove it and make it into its own post.
Given two groups there are probably mental differences.
More interesting is are the distributions bimodal and how much have they changed in e.g. last 100 years.
If the distributions are not bimodal or change relatively strong with time then a simplistic view of "women X, men Y" won't work.
Agreed. I'm very tired of articles which say "Hey look! There's a difference" without getting into the amount of individual difference or group overlap.
I agree. I'm also tired of "Hey look! There's overlap between the distributions, so let's pretend the difference doesn't matter!"
A simple example is height. On average men are taller than women.
But most of the time making a men=tall, women=short simplification does not make sense. It makes more sense to provide multiple sizes for both women and men.
And if providing only a very limited selection of sizes (e.g. hospital clothing) it makes sense to provide different unisex sizes rather than one for men and one for women.
And while we're busy being tired, I'm really tired of no research by anybody (so far as I know) about keeping reactions to ideas one has about group differences in proportion to what one actually knows instead of exaggerating the size or extent of the differences.
It took rather a lot of hammering to get to the idea of atypical women.