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Re:Harvard discrimination lawsuit: data show penalization of... by JumpCrisscross on Sunday June 17, 2018 @10:03PM (#17335455)
> All of those subjective ratings should be heavily correlated

I wouldn't go so far. If your measures always correlate, why have separate measures? The point is when one measure disagrees with the others, it should say something meaningful. In this case, the disagreement appears to say "this student is Asian."

Re:Harvard discrimination lawsuit: data show penalization of... by albntomat0 on Sunday June 17, 2018 @10:09PM (#17335494)
My understanding of it is that they are multiple samples of the same underlying distribution (the applicant's subjective characteristics). Multiple references who know/have interacted with the applicant attest to his/her personality strengths & weaknesses, and the average of all of them should result in an accurate measure of the person. If one of your "sensors" consistently measures lower than the grouping of the others, then you look into why that one is giving faulty readings, if it does so over a large sample size.