The usual model of discrimination: women face a higher bar to get hired. But this would mean that, conditional on getting hired, they’d outperform—and thus get more equity. For the model to work, you have to posit more discrimination from employers after the hire than before.
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The model also works if you assume that employers both discriminate against women and discriminate extra against competent women. That would work.
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Except that that means the rewards for breaking ranks and treating women equally are even higher than anticipated. The Forbes 400 should be 200 Grl Power CEOs, 195 Badass Bitchin’ VCs and 5 very lucky widowers.
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TLDR the data are consistent with the idea that male/female variance in outcomes is due to factors other than discrimination. And the journos are consistently wrong.
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Shout-out to
@HelloAngels for publicizing this data on why the gender gap is less likely to be due to discrimination, and thanks to@danprimack for signal-boosting it into my inbox. Without your data-driven efforts, I would be less convinced that sexism in tech is exaggerated.Show this thread
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