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Thing is, I sense you are not able to refute the author's argument, and instead resort to claiming it's "completely irrelevant" and "deliberate and malicious".
by Pilfer 9y ago
Thing is, I sense you are not able to refute the author's argument, and instead resort to claiming it's "completely irrelevant" and "deliberate and malicious". Claims which, frankly, do not refute the author's argument. Just walk through it:
Claim 1: "we don't have 50% representation of women in tech and leadership."
Let's narrow this down to just Google. I believe we both agree on this claim, it comes from Google's diversity reports.
Claim 2: There exist "Differences in distributions of traits between men and women"
This is a contentious point, but I believe this is well supported and cited by studies from here https://en.wikipedia.org/wiki/Sex_differences_in_psychology#Personality_traits https://en.wikipedia.org/wiki/Sex_differences_in_psychology#... and also studies provided in the author's treatise. We do observe differences in distributions of traits between men and women, who are of adult age and could work at Google.
I don't see a reason why employee's at Google are exempt from these studies. I argue [Claim 2] applies to Google employees.
Claim 3: [Claim 2] may in part explain [Claim 1]
I don't see how this could be offensive. Claim 3 is simple induction from Claim 1 and Claim 2. We observe differences in distributions of traits between men and women, so why wouldn't we see these traits show up in the percentage representation of women in tech?
- zzalpha 9y agoThe problem is that the gender differences you're referring to cannot, in aggregate, explain the 70/30 bias toward men in the industry. There's a real similarity to the global warming debate, here. There are many factors that affect global mean temperature. For example, over the very long term, the sun will get brighter. But that can only account for an astonishingly tiny fraction of the warming observed on the planet. Someone who wishes to debate honestly would admit that, while there are many factors that affect global mean temperature, the rise on CO2 concentration in the atmosphere is significant, and has a demonstrable effect on temperature, making it by far the strongest influencer. Someone who wishes to debate dishonestly will use these other explanations as a method to muddy the debate and try and turn attention toward lesser factors that cannot explain the whole effect. Now, if you look at this current "debate", yes, there are undoubtedly biological gender differences that can explain some male/female bias in engineering (among many other disciplines). But no serious psychologist or sociologist would claim that those differences can account for the dramatic real world bias in the industry. It simply doesn't follow. So to claim those gender differences lie at the root of bias in the industry is a distraction. At best it's a gross misunderstanding of the science. At worst, it's a deliberately dishonest attempt to muddy the waters and confuse the debate. My bet is it's more the former than the latter... reading the text of the memo, my bet is that this guy has an antiquated and/or simplistic understanding of gender bias and population statistics, and has found himself falling victim to the dangers of confirmation bias. But let's call a spade a spade, here: he doesn't really know what he's talking about (there's a cognitive bias I'm looking for here... where someone who's an expert in one area therefore believes they're an expert in other, unrelated areas... it's not Dunning-Kruger but it's something like it).
- Pilfer 9y agoI also sense you also are not able to refute the author's argument. You don't deny that the author's points, that is the Differences in distributions of traits between men and women, could possibly explain a percentage points shift in either direction. The author cites scientific studies sources that explain how "Women, on average, have more openness directed towards feelings and aesthetics rather than ideas [1]. Women generally also have a stronger interest in people rather than things[2], relative to men (also interpreted as empathizing vs. systemizing [3] )." These scientific studies support the idea that when given the choice, women will chose to work in fields more in line with their desires. And a it's 'very common and well-replicated finding that the more progressive and gender-equal a country, the larger gender differences in personality become' [4]. What do we observe of this effect in the real world? Women make up 90% of nurses, 80% of new veterinarians, 75% of new psychologists, about 75% of new pediatricians, about 74% of forensic scientists, about 72% of medical managers, and 68% of new biologists. [4] Every women working in these fields is one less that could be working in tech. The author argues that "Differences in distributions of traits between men and women may in part explain why we don't have 50% representation of women in tech and leadership." Is this not a partial explanation of the phenomena we are observing? A common theme I've noticed among critics is they like to throw around terms like "gross misunderstanding of the science" "no serious psychologist" "deliberately dishonest attempt" but don't bother disproving the scientific argument with scientific studies or statistical evidence of their own. [1] https://en.wikipedia.org/wiki/Sex_differences_in_psychology#Personality_traits https://en.wikipedia.org/wiki/Sex_differences_in_psychology#... [2] http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1751-9004.2010.00320.x/abstract http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1751-9004.... [3] https://en.wikipedia.org/wiki/Empathizing%E2%80%93systemizing_theory https://en.wikipedia.org/wiki/Empathizing%E2%80%93systemizin... [4] http://slatestarcodex.com/2017/08/07/contra-grant-on-exaggerated-differences/ http://slatestarcodex.com/2017/08/07/contra-grant-on-exagger...
- zzalpha 9y agoIs this not a partial explanation of the phenomena we are observing? Partial? Sure. But while these tendencies have measurable effects at the population level, at an individual level they're statistically very small, multivariate effects. They cannot, on their own, explain away even a significant portion of the gender imbalance in any of the industries you cite. It particularly makes no sense when you consider that gender balance in many industries have changed dramatically over time, something that shouldn't happen if biology was the primary determinant of career path. I've commented elsewhere on this topic if you'd like to see a slightly more thorough treatment and some related citations... it's a waste of my time to repeat it here and I'd probably not do the full discussion justice in any case.