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by roguecoder 5076 days ago
Who said anything about lowering the bar for anyone? There is no bar to attend most hackathons, no qualifying heats or even resume screening.

You also assume that lowering the bar inherently attracts less-qualified people than the marginal alternative participant. That is not true unless the outcome you care about is whatever bar you are using to measure and people accurately self-assess (or universally apply). For example, there is a 1992 study that found that SAT scores were equally good at predicting success of women and men, but only within those groups. Women performed as well during college courses as men with SAT scores 50 points higher (http://her.hepg.org/content/1p1555011301r133/). In such a case in order to maximize total academic performance, you would need to compensate for that systematic discrepancy and lower the SAT bar for women: what you are actually doing is normalizing the predicted-college-performance bar. That would not maximize total admitted SAT scores, but might maximize the outcome the college actually cares about.
1 comments
yummyfajitas 5076 days ago
Who said anything about lowering the bar for anyone?

Cletus, in the post you replied to.

As for using gender as a predictor in admissions, you'd also need to penalize high scoring women (and reward the low scoring ones). I have no particular objection to any of this.

http://www.overcomingbias.com/2008/08/variance-induce.html

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anthonyb 5076 days ago
Mean SATs, not their variance. I don't think that overcomingbias link is really adding anything to the discussion.

The paper that roguecoder referenced is just pointing out that SAT scores are not a perfect predictor, and adjusting the intake based on gender is probably a good idea if you want to maximise the real effect (academic performance), rather than the predictor (SAT scores).

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yummyfajitas 5075 days ago
The Robin Hanson blog post points out the exact same thing. Why is a positive correction for women useful, but a negative one "not adding anything to the discussion"?

If you want to use gender as a predictor, it could be positive or negative.

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