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by theptip
1953 days ago
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Absolutely - and with a bit more work you could come up with some citations for “rate of affirmative action cases by industry” and bulk up that fact-based argument to the level of rigor that I’m advocating. My point was at the meta level that we should be using facts and evidence when we talk about this rather than saying “we just know we are right.” as the original commenter did. Worth noting though that your theory doesn’t actually have enough explanatory power to explain the interesting part of the data; one of the points in Grant’s original article (which Scott is arguing against) was this juicy graph: https://media-exp1.licdn.com/dms/image/C4E12AQGEJuKqIh95Ng/a... Note that female participation in CS increases along with other fields in the 70s, then something happens in 84/85 and participation plummets. Your theory would support a graph where CS never tracked with those other fields. But this is as clear an exogenous event as you are going to see in social science data. What happened in 84? Maybe there is an explanation in the affirmative action caseload? I didn’t look at that dimension but your theory (fleshed out with data) might shed some light on that. (Also note that this graph looks worse than it really is; total CS enrollment also plummeted in 84 due to a recession and so there is a confounding effect there.) Again, this is why data is so important in these discussions. The reality is way more complex than the “we know we are right” crowd appreciate; if you get this wrong then you won’t be able to fix the problem (or even identify the real problem). |
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If you are interested in this area then I would recommend reading the book Why Aren't More Women in Science?. It has 15 essays by experts debating the issue.
rayiner, a HN lawyer, also has some good posts that discuss affirmative action in law (https://news.ycombinator.com/item?id=21775576) (https://news.ycombinator.com/item?id=6875443).