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Very interesting article, and sort of depressing for me, specifically the conclusion of Wang et. al[0]. That if you're good at both math and communication, you

Very interesting article, and sort of depressing for me, specifically the conclusion of Wang et. al[0]. That if you're good at both math and communication, you choose a more social field over the mathematical one is almost a condemnation of the mathier fields. Then again, being good at math in high school as Wang et. al measures doesn't really translate to math in college, which is much more problem solving oriented than math in high school. That's something to keep in mind here, so the whole idea that they end up being spread more broadly and thus aren't concentrated in STEM as the socially dumb men are is a more convincing explanation, it really doesn't have to do with differences in ability, it's merely other factors, mainly which major they try first. How interesting. [0] http://www.cds.web.unc.edu/files/2014/10/not_lack_of_ability.pdf http://www.cds.web.unc.edu/files/2014/10/not_lack_of_ability...

pmarreck 9y ago
> That if you're good at both math and communication, you choose a more social field over the mathematical one is almost a condemnation of the mathier fields. I didn't see it that way. I saw it as: There's a market of "mathy" and "verby" jobs. Men can mainly only be good at the mathy ones. Women can be good at both. So women end up at the verby jobs simply by nature of market forces.
deleted 9y ago
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aidenn0 9y ago
It's more complicated than that, even with very simple models. Consider the toy model where there are two types of talent, "A" and "B" and that society benefits roughly equally, but sub-linearly, from productivity added to "A" talent jobs and "B" talent jobs. Consider the following talent distribution: A | B -------------- Men |1 | 2 Women |2 | 2 As society tends towards the maximally efficient it will tend towards women in all A jobs and men in all B jobs, despite the fact that women are just as good at B jobs. This obviously is a toy model, but it shows that even very simple assumptions can lead to very odd outcomes.
- solidsnack9000 9y ago
  It would be great if you could (a) work through how that final distribution is more optimal and (b) explain why the number of men sums to 3 but the number of women sums to 4.
  - aidenn0 9y ago
    Sorry, the numbers are a measure of talent; so from that table, if a man were to work a year in an "A" field, he would generate 1 unit of production, but if he were to work a year in a "B" field he would produce 2 units of production. A woman would produce 2 units of production regardless of whether it is in an "A" or "B" field. In many real-world cases you get diminishing returns for more production. Let's say it's a square-root return, so 16 units of production in "A" is twice as good as 4 units of production in "A" (if you do the math with other diminishing returns like logarithmic you see a similar outcome). Consider a population of 8 men and 8 women. If they are equally distributed between jobs there are 12 units of production of "A" and 16 units of production of "B" for a total value of sqrt(12)+sqrt(16) ~=7.5 units of total value. If instead all women work in "A" jobs and all men work in "B" jobs, then you will see 16 units of production in each, for a total value of 8 units. The most pessimal would be the reverse of that and it would generate ~6.8 units of value.
    - solidsnack9000 9y ago
      Thanks for explaining. That makes a lot of sense. I was obviously reading the table wrong and had a sense that there was a good explanation underlying things here, but no real intuition about it.
- noobermin 9y ago
  I sort of agree with you though, I'm not sure we disagree. See my second paragraph, though, "B" in this case actually isn't a great measure of how well you'd do STEM but is more of a determinant of whether you'd try STEM out in the first place over the "A" fields. And yes, after that, market like forces might keep them or pull women to "A" fields eventually.
jhanschoo 9y ago
To build on sibling comment by pmarreck, perhaps the model this leads us to abduce is this: everyone prefers more social careers when they are beginning to choose one, but those who find themselves less verbally fluent self-distinguish by going into STEM fields.

pmarreck 9y ago

> That if you're good at both math and communication, you choose a more social field over the mathematical one is almost a condemnation of the mathier fields. I didn't see it that way. I saw it as: There's a market of "mathy" and "verby" jobs. Men can mainly only be good at the mathy ones. Women can be good at both. So women end up at the verby jobs simply by nature of market forces.

deleted 9y ago

[deleted]

aidenn0 9y ago

It's more complicated than that, even with very simple models. Consider the toy model where there are two types of talent, "A" and "B" and that society benefits roughly equally, but sub-linearly, from productivity added to "A" talent jobs and "B" talent jobs. Consider the following talent distribution: A | B -------------- Men |1 | 2 Women |2 | 2 As society tends towards the maximally efficient it will tend towards women in all A jobs and men in all B jobs, despite the fact that women are just as good at B jobs. This obviously is a toy model, but it shows that even very simple assumptions can lead to very odd outcomes.

solidsnack9000 9y ago
It would be great if you could (a) work through how that final distribution is more optimal and (b) explain why the number of men sums to 3 but the number of women sums to 4.
- aidenn0 9y ago
  Sorry, the numbers are a measure of talent; so from that table, if a man were to work a year in an "A" field, he would generate 1 unit of production, but if he were to work a year in a "B" field he would produce 2 units of production. A woman would produce 2 units of production regardless of whether it is in an "A" or "B" field. In many real-world cases you get diminishing returns for more production. Let's say it's a square-root return, so 16 units of production in "A" is twice as good as 4 units of production in "A" (if you do the math with other diminishing returns like logarithmic you see a similar outcome). Consider a population of 8 men and 8 women. If they are equally distributed between jobs there are 12 units of production of "A" and 16 units of production of "B" for a total value of sqrt(12)+sqrt(16) ~=7.5 units of total value. If instead all women work in "A" jobs and all men work in "B" jobs, then you will see 16 units of production in each, for a total value of 8 units. The most pessimal would be the reverse of that and it would generate ~6.8 units of value.
  - solidsnack9000 9y ago
    Thanks for explaining. That makes a lot of sense. I was obviously reading the table wrong and had a sense that there was a good explanation underlying things here, but no real intuition about it.
noobermin 9y ago
I sort of agree with you though, I'm not sure we disagree. See my second paragraph, though, "B" in this case actually isn't a great measure of how well you'd do STEM but is more of a determinant of whether you'd try STEM out in the first place over the "A" fields. And yes, after that, market like forces might keep them or pull women to "A" fields eventually.

jhanschoo 9y ago

To build on sibling comment by pmarreck, perhaps the model this leads us to abduce is this: everyone prefers more social careers when they are beginning to choose one, but those who find themselves less verbally fluent self-distinguish by going into STEM fields.