-[quantifying the two-type effect:
-Lippa 2000 "Gender-Related Traits in [...]"
-2.70 effect of femininity for gay vs. not-day and 1.07 for "any" vs. "no" attraction to men
-mean GD score for non-lesbian women as 0.31; mean score for gay men was 0.30!
-—oh, maybe I want to be using Study 2, which had a better sample of gays
-GD occupations in study 2
-gay men are at .48 (.14); straight women at .36 (.13); straight men at .68 (.12)
-that's d=–1.61 between gay and straight men
-a gay man only needs to be 1 standard deviation (.48-.36 = 0.12) more feminine than average to be as feminine as a straight women
-whereas a straight man needs to be (.68-.36 = 0.32) 0.32/0.12=2.67 more feminine than average to be as feminine as a straight woman—that's rarer, but not impossible
-
-In percentile terms, 1-norm.cdf(1) = 0.15 of gay men are as feminine as a woman
-whereas 1-norm.cdf(2.67) = 0.003 of straight men are
-that's a likelihood ratio of 50 ... but the prior is not that far from 50:1 in the other direction! They cancel out!!
-
-For concreteness: what does the Bayes net spit out if 3% of men are gay, and 5% are AGP, and whatever other assumptions I need to make this work?
-Suppose gays transition if they're 2-sigma feminine ...
+Ultimately, the reader cannot abdicate responsibility to think it through and decide for herself ... but it seems to _me_ that all six arrows in the graph are things that we separately have a pretty large weight of evidence for, either in published scientific studies, or just informally looking at the world.