explain a large share of the effects found by audit studies that claim what they found is racial discrimination when really their design doesn't allow to rule out statistical discrimination and class-based discrimination.
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On the main problem identified by Heck though, I think there is a guy who devised a method which he claims solves it (was it Neumark?), but I haven't read his paper yet.
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I am confused. Certainly evid for "stat discrim" exists. I do not see how evidence for said *existence* constitutes any explanation for audit studies, which personal info constant. I hope next tweet conveys why I don't follow your argument
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Me: discrim in audit studies replicate* You: But much is explained by stat discrim Me: Got evidence? You: Lots of evid. of stat discrim Me: But your claim was not "there is evid of stat discrim." Your claim was "stat discrim explains audit studies." I still see no supporting evid
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* To get to the point that we agree that that orig statement was actually true, we had to dance through
@pnin1957 's tweets seeming to contest that, but which we now agree was simply a different point that did nothing to contest "discrim in audit studies replicates."1 reply 0 retweets 1 like -
Replying to @PsychRabble @pnin1957
Okay here is my reasoning. You have plenty of audit studies that find discrimination, but their design usually doesn't allow you to tell whether it's racial discrimination, statistical discrimination or class-based discrimination. Now, we also have plenty of evidence that there
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Still not following. Many audit studies hold constant work history (for job apps), or credit rating (for housing apps). How does that not rule out (at least most of, maybe all of) stat discrim?
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Replying to @PsychRabble @phl43
Not treating blacks and whites with the same credit score the same is an excellent example of statistical discrimination:pic.twitter.com/6JWQZat7bf
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Any deviation from perfect measurement causes some regression towards the group mean. Hence, since some amount of measurement error is unavoidable, rational agents should not use exactly the same score cutoffs across groups.
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Yep, except that it's generally illegal
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The most socially acceptable solution is thus to develop better measurements, or more add more predictors. Both will attenuate the problem, though not completely remove it.
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The idiot social justice approach is just the opposite, e.g. "ban the box".
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