Is There Anything Good About Men

For now,
the point is that it explains how we can have opposite stereotypes. Men go to
extremes more than women. Stereotypes are sustained by confirmation bias. Want
to think men are better than women? Then look at the top, the heroes, the
inventors, the philanthropists, and so on. Want to think women are better than
men? Then look at the bottom, the criminals, the junkies, the losers.

            In an
important sense, men really are better
AND worse than women.

            A pattern
of more men at both extremes can create all sorts of misleading conclusions and
other statistical mischief. To illustrate, let’s assume that men and women are
on average exactly equal in every relevant respect, but more men at both
extremes. If you then measure things that are bounded at one end, it screws up
the data to make men and women seem significantly different.

Consider grade point average in
college. Thanks to grade inflation, most students now get A’s and B’s, but a
few range all the way down to F. With that kind of low ceiling, the
high-achieving males cannot pull up the male average, but the loser males will
pull it down. The result will be that women will get higher average grades than
men — again despite no difference in average quality of work.

opposite result comes with salaries. There is a minimum wage but no maximum.
Hence the high-achieving men can pull the male average up while the
low-achieving ones can’t pull it down. The result? Men
will get higher average salaries than women, even if there is no average
difference on any relevant input.

            Today, sure
enough, women get higher college grades but lower salaries than men. There is
much discussion about what all this means and what should be done about it. But
as you see, both facts could be just a statistical quirk stemming from male

That’s pretty interesting. Sometimes, I try to think of thoughts I’m not allowed to think, but it’s so hard since things that you’re whispered to be true over and over again, you’ve just come to accept it.

‘Maybe there is a disparity there’, rather than, ‘maybe it’s a statistical aberration’.


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