It is interesting to me that this major claim is the one that has no citations supporting it. The other references detailing multivariate distinctions in gender morphology all go to pains to point out that most univariate measures have huge amounts of overlap, and pull the distinctions out of groupings of variables.
So why did Debrah Soh neglect to provide supporting citations for the claim that societies with greater gender equity have greater gender career gaps, given that it's the one most central to supporting the Anti-Diversity Manifesto?
Is Debrah going to dispute the claim that Engineers — having to deal with people — need "soft" skills? Is she going to claim that all STEM work is necessarily playing with wheeled toys?
How does Debrah explain that "Gender equality closes the math gap[1]"?
"For science literacy, while the USA showed the largest gender difference across all OECD nations, d = .14, gender differences across OECD nations were non-significant, and a small female advantage was found in non-OECD nations, d=-.09."[2]
It's one thing to be "good at mathematics", quite another to be "a good engineer."
Nobody who participates in quota systems or diversity hiring believes that what they are doing is sustainable in the long term. The point of attempting to hire more people from under-represented portions of the populace is to counter-balance institutionalised sexism.
Debrah Soh does raise one important point: sexism doesn't come from knowledge of a subject, but what we do with that knowledge.
So why did Debrah Soh neglect to provide supporting citations for the claim that societies with greater gender equity have greater gender career gaps, given that it's the one most central to supporting the Anti-Diversity Manifesto?
Is Debrah going to dispute the claim that Engineers — having to deal with people — need "soft" skills? Is she going to claim that all STEM work is necessarily playing with wheeled toys?
How does Debrah explain that "Gender equality closes the math gap[1]"?
"For science literacy, while the USA showed the largest gender difference across all OECD nations, d = .14, gender differences across OECD nations were non-significant, and a small female advantage was found in non-OECD nations, d=-.09."[2]
It's one thing to be "good at mathematics", quite another to be "a good engineer."
Nobody who participates in quota systems or diversity hiring believes that what they are doing is sustainable in the long term. The point of attempting to hire more people from under-represented portions of the populace is to counter-balance institutionalised sexism.
Debrah Soh does raise one important point: sexism doesn't come from knowledge of a subject, but what we do with that knowledge.
1: https://www.sciencenews.org/article/gender-equality-closes-m... 2: http://journals.plos.org/plosone/article?id=10.1371/journal....