He's saying it's borderline irresponsible because Neil is publishing correlations--which he actually calls predictors--that in no way have any statistical valid

He's saying it's borderline irresponsible because Neil is publishing correlations--which he actually calls predictors--that in no way have any statistical validity, and further causes baseless damage by reinforcing negative stereotypes that a group of people struggles against daily. In the one area he addresses sample size, all he says is that the limited sample size restricts the ability to find positive predictors. That's stupid. Limited sample size also severely restricts ability to claim significant correlation (which is implied in claiming predictive power). Nobody is claiming that statistically rigorous data, which show that the women self-selecting for applications in this job post can't pass the qualifications, should not be made public; the claim is that claiming predictive power in a sample of two that hurts a negatively stereotyped group is irresponsible. And it is. If I were to go out on the street, test 30 random people, two of whom happened to be black, and who randomly had lower tested IQ than the rest of the sample, would it be responsible for me to claim that being black is a predictor of lower IQ? It's the same deal. Do a proper study or don't claim predictive power. Particularly when being statistically foolish could hurt people.