Women in science

The Science on Women and Science, is a collection of essays by researchers who disagree on why women lag behind men in science careers. Is it gender bias? Differences in ability or interest? Sean Cavanagh summarizes on Curriculum Matters:

Some of the essayists, like Spelke and Ellison, argue that research shows that men and women have the same intrinsic cognitive abilities and motivation for math and science careers. . . . The evidence shows that gender stereotypes are having an impact on leading women away from math and science fields, the authors explain.

But others, like authors Jerre Levy and Doreen Kimura, have a different take. . . . They say research has shown a connection between genetic and hormonal differences between males and females, which affect behavior and choice of occupation.

There are more men at the very top and the very bottom of the bell curve.  “In consequence, there would still be more males than females who meet even minimum standards to be academic engineers, physical scientists, or mathematicians, and many more men than women with exceptionally high levels of talent,” Levy and Kimura write.

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  1. This is the hypothesis that got Larry Summers in hot water at Harvard. Average ability is the same, but males have a higher variance.

    I would not be surprised if this correlated to testosterone levels rather than gender.

    I would also not be surprised if gender stereotypes and discrimination were bigger factors.

  2. Armchair Non-Biologist says:

    I’m going to ruminate on something I know absolutely nothing about. WARNING: I’m completely talking out my rear end here. I’m not a biologist. I don’t even like biology. I’m not an anthropologist, either. But I was thinking some stuff over….

    Male variability seems to make genetic sense (i.e., good for the species) if you consider the notion that the strongest, best males will reproduce with more than one partner.

    If you think of a tribe of humans as an organism, it’s going to want the best, strongest, most cunning warriors it can field to deal with opposing tribes and packs of nasty animals. Men are the tip of the species spear, so there’s an “evolutionary imperative” (in a non-teleological sense) towards making sure that the guys out on the end of the spear are the hardest, meanest, smartest creatures around.

    Tribes that had high genetic variability in their males will have more runts (who die quickly), but they will also have more Achilleses, more Hectors. In the high-stakes crucible of fights over water, territory, and females, sometimes all you need are minor edges…. a few warriors who are just a little bit better. Think of it as a genetic arms race. The tribe with the most 3-sigma positive deviations wins.

    Or, think of it as a dice game. Tribe A has a standard square die, but with the following numbers on it: 3, 3, 4, 4, 5, 5. Tribe B has a die with these numbers: 1, 2, 3, 4, 5, 6. The two tribes go to war. It seems like Tribe A might have an advantage, because it’s average roll is going to be 4, but Tribe B’s is going to be 3.5. Put your money on tribe A, anyone????

    But that’s not actually how it works. When Tribe B rolls a 6, that 6 gets to keep playing… probably taking out four or five of Tribe A’s rolls. And Tribe B, because it leaves infants out to die, gets to IGNORE its “1” rolls, and maybe even its 2’s. And Tribe B’s 6’s are slightly more likely to cause another 6 to be rolled on the next roll of the dice because of inheritability. From Tribe B’s perspective, all that matters is rolling as many 6’s as possible. Over milennia, Tribe B’s advantage is going to grow and grow precisely because of its ability to produce 6’s in greater numbers than Tribe A.

    This explains why there wouldn’t be as strong a corresponding benefit — evolutionarily speaking — to having the same variability in women. Such variance could have existed, and it might still exist in certain subsets of the population, but there wasn’t millions of years of pressure weeding out populations that didn’t produce superstar women, because a woman can’t have 20 kids all at the same time. A guy can roll the dice, as it were, a WHOLE BUNCH of times. And remember… we’re not worried about all the times you roll “1” or “2”. All we care about are the number of “6’s” that you roll.

    So that’s me, speculating about something I know absolutely nothing about. But that’s what the internet is good for, no?

  3. I think the biggest factor is the perceived family-unfriendliness of STEM careers. Men are more willing than women to spend their 20’s and early 30’s toiling away long hours in the lab. One of the major reasons I dropped off the pre-med track was because I wanted to have a larger family.

  4. Crimson…partner track in a law firm also involves toiling away long hours (though not in a lab), yet there are an awful lot of women pursuing legal careers, including careers at top and very-demanding firms.

  5. Here’s an explanation I’ve seen — sorry, I can’t remember where — for men’s greater variance. Women have two X chromosomes; men have one. The X chromosome includes genes that influence our intelligence. Simplifying outrageously, women get the average of those two chromosomes; men don’t. Hence, there is less variance among men, in intelligence, and in other things.

    (The Y chromosome is quite small and doesn’t do much other than determine sex. Incidentally, this also means that, on the average, sons are a little more closely related to their mothers than daughters are.)

  6. Meant to say: “Hence there is more variance among men, . . ”

    Sorry about that.

  7. The law allows for the ridiculous leftist bullshit inherent in gender studies, ethnic studies, etc.

    Science doesn’t. Or least usually doesn’t.

    I wonder if this has anything to do with the numbers?

  8. I would not be the least surprised that more women decide they’ve got something else they’d prefer to do.

    Here is my question: why should I care? Is there important math being missed, “women’s math”, that is going unexplored due to this “lack” of women in academic math?

    To the extent that specific, individual women are being discriminated against, the state of things is bad. But simply noting that there are more men than women in a field does not per se prove injustice of some sort.

    Is it injustice that elementary education is overwhelmingly female? Does anybody whining about the paucity of females in particular academic fields also complain about that?

  9. “partner track in a law firm also involves toiling away long hours (though not in a lab), yet there are an awful lot of women pursuing legal careers, including careers at top and very-demanding firms.”

    The difference is that earning a PhD. typically takes a LOT longer than earning a J.D. A female lawyer can be done with her education by 24 and possibly make partner by 30. A female scientist might not get out of school until 30 and then be up for tenure at 37. That’s a big difference for women who want to have children.

  10. Soapbox0916 says:

    I would be a female in a science field if I could get a science job in my hometown. I had no trouble working long hours in the lab in the past and I don’t buy the argument that women are less willing to put in the time. Flexibility is more of an issue. Women such as myself want to be nearby family and that could be a gender difference that women stereotypically value family connections more than men. I don’t know if I believe that for women in general, even though it is true of me.

    I moved back to my hometown to be near family, especially to be near my elderly parents, but I had to take a non-science job (working with homeless providers in government) as a trade-off for moving back and being able to live in my hometown. I do enjoy what I do for a living, but I took a very stereotypical female based social work type of job because it was the only type of professional job that I could get hired at, despite being a scientist with a master’s degree, in order to live in my hometown and be nearby family.

    (On a side note, I originally started out in science education, and I do help with education programs for the homeless and ex-offenders, but moving back to my hometown meant giving up being a scientist, and I loved being a scientist.)

  11. Perhaps this will be the next “crisis” for Mr. Obama to address and rectify.

  12. Roger Sweeny says:

    Armchair Non-Biologist,

    It seems to me that what drives your model isn’t a higher variance but a higher mean. That average of 4 is higher than an average of 3.5. Also, according to your model, the mean of Tribe A is going to get even higher because the 1s and 2s are being weeded out. This will also have the effect of *lowering* variance.


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