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gjm comments on Open thread, 7-14 July 2014 - Less Wrong Discussion
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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.
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.
I've seen this said before (notably, Larry Summers took a lot of heat for saying it) and it seems like the kind of thing that might well be true, but I've never seen the actual numbers. Have you actually done the calculations?
If you just want some calculations, look at La Griffe: http://www.lagriffedulion.f2s.com/women_and_minorities_in_science.htm and http://www.lagriffedulion.f2s.com/math.htm / http://www.lagriffedulion.f2s.com/math2.htm
(I haven't checked his numbers or looked for more mainstream authors, but then again, would you expect to find many papers by prominent authors doing the exact calculation you want, especially post-Sumners?)
You say that as if I'm asking for something specific and unusual, but all I'm actually doing is responding to "If you do the calculations you find X" with "That's interesting; have you done those calculations or seen someone else do them, then?".
The problem is, I want to see someone other than La Griffe do the numbers and I'm not happy relying on him.
I don't know who he is, I haven't gone through his derivations or math, I don't know how accurate his models are, he uses a lot of old sources of data like Project Talent (which may or may not be fine, but I don't have the domain expertise to know), and the one piece of writing of his I've really gone through, his 'smart fraction' doesn't seem to hold up too well using updated national IQ data from Lynn (me and Vaniver tried to reproduce his result & update it in some comments on LW).
But the problem is, given the conclusion, I am unlikely ever to see someone from across the ideological spectrum verify that his work is right. (Whatever the accuracy of his own arguments, La Griffe does a good job tearing apart one attempt to prove there is no variance difference, where the woman's arguments show she either doesn't understand the issue or is being dishonest.)
Your third link begins with the Griffe taking numbers from Janet Hyde, who is on the opposite end of the spectrum. The difference is that she downplays the magnitude of the standard deviation difference. Isn't the main concern the source of the numbers, not the calculation? It's just a normal distribution calculation.
(I don't actually believe that intelligence is normally distributed, so I don't believe the argument.)
If you don't think intelligence is normally distributed, isn't that a problem for how true his results are and why one might want third-parties' opinion? And I'm not sure that affects his rank-ordering argument very much; that seems like it might be reasonably insensitive to the exact distribution one might choose.
OK, I understand. (I share your frustration, would count as "from across the ideological spectrum", and have at least a good subset of the necessary skills, but probably lack the time to try to rectify the deficit myself.)
I got the calculations from La Griffe, linked by gwern in a sibling comment. (For completeness, [1], [2], [3].) I have a vague recollection of checking them myself at some point.
OK. Thanks.