bramflakes comments on Open thread, 7-14 July 2014 - Less Wrong

2 Post author: David_Gerard 07 July 2014 07:14AM

You are viewing a comment permalink. View the original post to see all comments and the full post content.

Comments (232)

You are viewing a single comment's thread. Show more comments above.

Comment author: Vaniver 13 July 2014 01:50:45AM *  6 points [-]

The argument works just as well

I feel like the argument is slicing the problem up and presenting just the worst bits, when we need to consider the net effect on everything. This reminds me of a bioethics debate about testing error and base rate of rare lethal diseases: if five times as many people have disease A than disease B, but they look similar and the tests only offer 80% accuracy,* what should we do if the treatment for A cures those with A but kills those with B, and vice versa?

The 'shut up and multiply' answer is "don't give the tests, just treat everyone for A," as that spares the cost of the tests and 5/6ths of the population lives. But this is inequitable, since everyone with disease B dies. Another approach is to treat everyone for the disease that they test positive for- but now only 4/5ths of the population lives, and we had to pay for the tests! Is it really worth committing 3% of the population to the graveyard to be more equitable? If one focuses on the poor neglected patients with B, then perhaps, but if one considers patients without regard to group membership, definitely not.

*Obviously, the tests need to be dependent for 80% to be the maximal possible accuracy.

And people didn't notice the good blacks should be in the office and promote them at a higher rate to make up for it, either.

I don't know if it's possible to test this, and specifically it's not obvious to me that we need racial bias to explain this effect. That is, widespread cognitive stratification in the economic sphere is relatively new (it started taking off in a big way only around ~1950 in the US), and if promotions were generally inefficient, it's hard to determine how much additional inefficiency race caused.

These comparisons become even harder when there are actually underlying differences in distributions. For example, the difference in mean male and female mathematical ability isn't very large, but the overwhelming majority of Harvard math professors are male. One might make the case that this is sexism at work, but for people with extreme math talent, what matters much more than the difference in mean is the difference in standard deviation, which is significantly higher for men. If you take math test scores from high schoolers and use them as a measure of the population's underlying mathematical ability distribution and run the numbers, you predict basically the male-female split that Harvard has, which leaves nothing left for sexism to explain.

Comment author: bramflakes 13 July 2014 11:23:04AM 0 points [-]

Kind of offtopic but regarding male-female intelligence differences - in Britain at least, girls seem to consistently outperform boys in school math exams, which would imply there is a mean difference, in the opposite direction.

Comment author: gwern 13 July 2014 05:11:52PM *  5 points [-]

It might, but there are subtleties you have to take into account. For example, ceiling effects will hide the claimed effect, and if there's not enough floor, can even produce a lower mean.

Imagine you have a test of 10 4-multiple-choice questions, male mean = female mean but males have higher variance, and the average student's score on the test would be 8, so lots of students score a perfect 10 but you would have to be retarded to score <=2. What will the mean by gender look like under this scenario? Since the male variance is higher, there will be several times more near-retarded boys than girls scoring in the lower ranks like 3-4; there will nearly as many normal boys as normal girls with normal scores like 7-9; and the rest will score 10 - but the many more boys than girls who are far out on the tail (are genius at maths) will also score 10 and look like fairly ordinary types. So the dim boys drag down the mean of all boys, the ordinary boys by definition match their girl counterparts, while the geniuses can't show their stuff and might as well have not been tested at all; and so on net, it looks like the boys perform worse than the girls even though they actually are the same on average and have a higher variance. This is because I invented a test which is able to pick up on the differences among the low-performers (by devoting 7 questions to them) but not among the high-performers (just 2 questions), and this favors the group with the least representation among both tails (females).

And most real-world exams are uninterested in making very fine gradations among the top 1% of students like you need to if you want to answer questions about 'how many female Fields Medalists - top mathematician in the entire world - should there be?' because with non-adaptive tests you would have to force the 99% of ordinary people to slog through endless reams of questions they have no idea about. (American schools have no incentive to look because they are not evaluated under No Child Left Behind based on how many world-class students pass through their halls, they're evaluated on the average student and especially the minorities.)

Other issues include to what extent those exams are based on class grades (the usual situation is boys do worse on grades, better on exams, because grades measure how much you can ingratiate yourself to your teacher by things like sitting still and doing even the most tedious moronic homework each and every time) and whether the exam are being administered after puberty where the increased variance is expected to manifest itself.

Comment author: bramflakes 14 July 2014 12:19:36AM *  0 points [-]

Thanks for the explanation. The skill ceiling/floor argument makes sense for GCSEs, but I'm not sure how well it works for A-Levels. Boys only outperform girls at the very very top end, and despite the complaints that the ceiling isn't high enough, I don't think it can account for all the discrepancy (he said, remembering his bad stats intuition).

Maybe it's higher male variance and higher female mean?

Class grades also count for zilch in both, it was all exams last time I checked.

Comment author: gwern 14 July 2014 12:53:28AM *  2 points [-]

Boys only outperform girls at the very very top end,

I'm not sure I understand your link. If 43.7% of people score an A and that's the highest score, then it's definitely not 'very very top end' because that means it has almost zero information about anyone who is above-average (much less the extremes like 1 in 10k). And the Criticism section seems to accuse A-levels of a severe ceiling effect:

It has been suggested by The Department for Education that the high proportion of candidates who obtain grade A makes it difficult for universities to distinguish between the most able candidates.

Incidentally, notice the lowest grade: almost twice as many males as females.

Comment author: bramflakes 14 July 2014 11:38:19AM *  1 point [-]

I'm talking about Further Maths. The A grade for that is the only one with more boys than girls. It's much harder, and only 8,000 people take it compared to 60,000 for the standard Mathematics exam.

Then again, the ceiling still only looks to be the top 6-7% of the people taking math A-Levels. I think you're right.

Comment author: Douglas_Knight 15 July 2014 09:41:40PM 1 point [-]

Percent passing is not very informative because those sitting the test have been preselected. According to this spreadsheet, 50% more boys take Maths and more than twice as many boys take further maths. Also, it claims that the A* rate is twice as high for boys, at both levels, though the A rate is the same (which is weird).

(the spreadsheet has several sheets, but the link should go to the correct one - gender)