@paulg Works only with infinite pools of applicants. If First Round funded 100% of elite college students, could still get same results
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@terzicigor In practice not. In practice there is a huge supply of people who went to elite colleges yet aren't very good.
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@paultoo Good point. Such a strange choice. I wonder what the numbers would look like with Uber included.Thanks. Twitter will use this to make your timeline better. UndoUndo
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@paulg cool to see you write about this use case for real diversity numbers.Thanks. Twitter will use this to make your timeline better. UndoUndo
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@paulg Problem: If one group *is* inherently better than another, you would expect better perf from that group even under fair selection -
@paulg So this test works for groups you expect to be roughly equal (men/women?) but not for those you expect to be different (colleges) - Show replies
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@paulg Did you come up with it? It is brilliant and I need to know who to credit -
@tommyjensen I didn't learn about it from someone else, but I would be surprised if no one else had thought of it.
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Thanks. Twitter will use this to make your timeline better. UndoUndo
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@paulg bias is not the only reason a subgroup can outperform. So your test can only say “there might be bias at play here”, at best.Thanks. Twitter will use this to make your timeline better. UndoUndo
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