In brief, we have seen tonight that the gender gap in mathematics has been stable for at least half a century; that sex differences in ability-distribution means and variance ratio are independent of race, culture and geography; that female math performance is closest to that of males in high-IQ countries; that culture plays a role in math performance, albeit small; and that the theory of Everyone accounts for all of the above.The rest of his highly statistical article says that the Math IQ of men is ~0.15 standard deviations (near 2.5 points) above that of women on average, but FAR more importantly, the variance in Math IQ of men is also on the order of 15% higher. This means that if the stdev of IQ for women is about 13.5, the stdev for men is about 16. This means that in order to have a math IQ near 150, it requires 3 stdev for men [(150-102)/16=3], but 3.75 stdev for women (150-99.5/13.5 = 3.75 ), which is something like a 8:1 ratio. We've seen that information before on this blog.
There is a second factor that La Griffe's post brings up as well:
A study6 by Lubinski and Benbow followed the careers of mathematically precocious youth from age 13 to 23. All were in the top 1% of mathematical ability. At age 23 less than 1% of the girls were pursuing doctorates in mathematics, engineering, or physical science, while almost 8% of the boys were. Equal aptitude not withstanding, girls pursued doctorates in biology at more than twice the rate of boys, and in the humanities at almost three times the rate of boys. For all these reasons, we should regard 29% [%age of females in top 1% math ability -- aretae] as an upper bound to the percentage of women in the technological work force. In practice, their numbers will be significantly less.So...what we have about women in technology is:
- Lower likelihood of very high ability
- Lower interest in the field
I would like to add a third factor that seems under-discussed. I claim to have unusual insight into the topic due to my elementary math instruction days combined with my willingness to talk HBD and a reasonable understanding of evolutionary pressures.
Men have a well-known lower risk-aversion than do women. This is both experimentally known AND evolutionarily required. For any non-monogamous species, the value of a female's taking a risk is massively lower than that of a man's taking risks (for high payoffs). See the professional poker world or the trading world for good examples.
The more advanced math and technical fields get, the more risk-preference makes a difference. The best math people find problems, noodle them a while, get them wrong several times trying to find a solution, and then having tried 15 wrong answers, finally find a correct one. The best programmers do this too. Physicists are in the same boat, as far as my limited experience goes, and engineers are defined as a profession by how fabulously good they are at learning from their mistakes: "Well, the third prototype didn't explode". Quants in the financial industry are wrong maybe more than they're right, but they're learning, even while trying to outwit EMH.
I wish to argue that in math...the number of different approaches you try is a massive indicator of your future ability. Someone who does exactly what the teacher says is never going to be a very good mathematician. However, doing exactly what the teacher says is great for arithmetic, and it will get you to better-than average for algebra. It won't get you very far at all in math research or most "contest math". Instead, the people with the best future in math tend to be the ones who learn the teacher's way, but also work to develop their own heuristics, their own shortcuts...the ones who really don't want to show the work, because there's a bit of intuition involved. For what it's worth, both in my teaching and in my interactions with math professors, students of mine, and student-peers in school...the willingness to take academic risk is both highly positively correlated with math ability AND a highly male trait.