Ah, that’s the issue: I don’t mean that it’s more likely than not, or P(E|S)>P(~E|S), just that it’s more likely than it would be otherwise, or P(E|S)>P(E)>P(E|~S).
Oh, right :)
As a distributional statement, it could be interpreted as any of “the male intelligence mean is larger than the female intelligence mean” or “the male intelligence variance is larger than the female intelligence variance” or “high male intelligence is more visible than high female intelligence,” because all of those are distributional tendencies that could have noticeable results along the lines of “men are smarter than women.”
Have you tried asking people what they mean? That might narrow it down.
In particular, the ground truth of higher male variance in intelligence is interesting because it results in both “men are smarter than women” and “men are dumber than women” being valid impressions, in the sense that there are more smart men than smart women and dumb men than dumb women! This is perfectly natural if you think in distributions, and it seems to me that both of those are memes that are common in the wider culture.
“X are dumber than Y” is a pretty universal “meme”. Just like “X are worse people than Y”, “X are more/less emotional than Y” and so on and so forth. Note that positive stereotypes of women usually emphasize their intuition, which is often seen as opposed to “intelligence”.
IOW, interesting, but probably coincidence, since it fits better with the known tendency to develop opposing stereotypes than academics foolishly ignoring sources of evidence.
Oh, right :)
Have you tried asking people what they mean? That might narrow it down.
“X are dumber than Y” is a pretty universal “meme”. Just like “X are worse people than Y”, “X are more/less emotional than Y” and so on and so forth. Note that positive stereotypes of women usually emphasize their intuition, which is often seen as opposed to “intelligence”.
IOW, interesting, but probably coincidence, since it fits better with the known tendency to develop opposing stereotypes than academics foolishly ignoring sources of evidence.