20 ms·

In the context of the memo, he followed the neuroticism claim with a suggestion to "make tech and leadership less stressful", in order to help make the workplac

by psyc 9y ago

In the context of the memo, he followed the neuroticism claim with a suggestion to "make tech and leadership less stressful", in order to help make the workplace more inclusive to women. You appear to assume that the whole thrust of the memo was to argue that women aren't suitable. The stated aim of the memo was to explore ways of reducing the gender gap, other than quotas. People are mad because about 4 statements out of 100 imply that women aren't suitable. The intention (road to hell and all that) seems to have been to say the reverse: that tech jobs don't suit women. Too fine a distinction to expect most people to make, I suspect.

sangnoir 9y ago
> In the context of the memo, he followed the neuroticism claim with a suggestion to "make tech and leadership less stressful", in order to help make the workplace more inclusive to women While appearing to be very scientific, the memo offers no science to backup the underlying assumption with that line of thought("The reason there is a gender gap is because women can't deal with the high-stress environments of tech/leadership"). This is a massive leap from neuroticism. If anyone has the science to back that assumption, I'll be happy to read it.
- pjscott 9y ago
  That's a leap that he explicitly encourages people not to make: populations have a lot of variation, and to look at a difference in means as a categorical difference, to convert "women have a higher population mean for trait X" into "women are more X", is wrong both mathematically and ethically. (... And, yeah, I feel kind of pedantic here, but on this particular topic the people who don't think about it in terms of probability distributions are doomed to talk nonsense, and getting this right actually matters. So.)
  - sangnoir 9y ago
    I was talking in terms of population & probability - but that's neither here nor there because ultimately the distribution of the traits don't matter when the traits are not correlated with success/failure (or representation in C.Sci). That is the leap I am referring to: I'm not prepared to take the same leap (gender traits -> outcomes) others are taking without seeing the supporting literature. edit: Rayiner's comment[1] explains the lack of scientific rigor way better than I did 1. https://news.ycombinator.com/item?id=16399052 https://news.ycombinator.com/item?id=16399052

by psyc 9y ago

sangnoir 9y ago

> In the context of the memo, he followed the neuroticism claim with a suggestion to "make tech and leadership less stressful", in order to help make the workplace more inclusive to women While appearing to be very scientific, the memo offers no science to backup the underlying assumption with that line of thought("The reason there is a gender gap is because women can't deal with the high-stress environments of tech/leadership"). This is a massive leap from neuroticism. If anyone has the science to back that assumption, I'll be happy to read it.

pjscott 9y ago
That's a leap that he explicitly encourages people not to make: populations have a lot of variation, and to look at a difference in means as a categorical difference, to convert "women have a higher population mean for trait X" into "women are more X", is wrong both mathematically and ethically. (... And, yeah, I feel kind of pedantic here, but on this particular topic the people who don't think about it in terms of probability distributions are doomed to talk nonsense, and getting this right actually matters. So.)
- sangnoir 9y ago
  I was talking in terms of population & probability - but that's neither here nor there because ultimately the distribution of the traits don't matter when the traits are not correlated with success/failure (or representation in C.Sci). That is the leap I am referring to: I'm not prepared to take the same leap (gender traits -> outcomes) others are taking without seeing the supporting literature. edit: Rayiner's comment[1] explains the lack of scientific rigor way better than I did 1. https://news.ycombinator.com/item?id=16399052 https://news.ycombinator.com/item?id=16399052