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> Read the link cited with that sentence and you might understand it better. It is saying that gender issues which affect men are not taken seriously an

> Read the link cited with that sentence and you might understand it better. It is saying that gender issues which affect men are not taken seriously and are discarded. I wonder what gender issue Damore found himself facing. Homelessness? Murder? And when he raised those issues he was labeled a misogynist? That doesn't seem to fit. It's hard to accept that there is nuance in the memo, because it's only found in broad sentences like this one: > 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. There's nothing wrong with this sentence. The trouble is that he never concretely addresses reasons for the gender gap other than innate traits. There is some nuance in his memo, but there isn't enough. What about all these documented biases? Surely these are affecting womens' careers too: * Men get better assignments. https://hbr.org/2013/09/women-in-the-workplace-a-research-roundup https://hbr.org/2013/09/women-in-the-workplace-a-research-ro... * People assume mothers to be inherently less competent and less committed than fathers. https://hbr.org/2013/09/women-in-the-workplace-a-research-roundup https://hbr.org/2013/09/women-in-the-workplace-a-research-ro... * Women negotiate as often as men, but face pushback when they do. https://womenintheworkplace.com/ https://womenintheworkplace.com/ * Women get less access to senior leaders. https://womenintheworkplace.com/ https://womenintheworkplace.com/ * Women ask for feedback as often as men, but are less likely to receive it. https://womenintheworkplace.com/ https://womenintheworkplace.com/ * Women get less useful feedback than men. https://hbr.org/2016/04/research-vague-feedback-is-holding-women-back https://hbr.org/2016/04/research-vague-feedback-is-holding-w... * Women get criticized more than men. http://fortune.com/2014/08/26/performance-review-gender-bias/ http://fortune.com/2014/08/26/performance-review-gender-bias... * Women are more frequently characterized as “too agressive”. https://www.wsj.com/articles/gender-bias-at-work-turns-up-in-feedback-1443600759 https://www.wsj.com/articles/gender-bias-at-work-turns-up-in... * Women leaders face higher standards and lower rewards than men leaders. http://www.catalyst.org/knowledge/double-bind http://www.catalyst.org/knowledge/double-bind * Women leaders are perceived as competent or liked, but rarely both. http://www.catalyst.org/knowledge/double-bind http://www.catalyst.org/knowledge/double-bind * Women’s code is accepted more often than men’s, but only if gender is hidden. http://www.bbc.com/news/technology-35559439 http://www.bbc.com/news/technology-35559439 Sure, he says that innate traits are only part of the cause. But the rest of his essay implies they are the primary cause.

zbobet2012 9y ago
His memo absolutely fails to mention the biases women deal with on a daily bases. It fails to mention how unjust such things can be and how they must make his female colleagues feel. And that such things are well supported by research. That failure makes his audience significantly less receptive, and puts them on the immediate defense. He should spend some serious time reading "Difficult Conversations" and other books of it's ilk. As much as he wants to avoid feelings, feelings always matter. Hence the justified accusation of his memo being "tonedef". And you are not considering the context in which it was written, or are missing key statements like: > For the rest of this document, I’ll concentrate on the extreme stance that all differences in outcome are due to differential treatment and the authoritarian element that’s required to actually discriminate to create equal representation. For him it is clearly table stakes that women are discriminated against. He doesn't feel the need to argue it because he, and the Google culture which he is addressing, finds it so imminently obvious. Something he states. Multiple times. Throughout the document. > Sure, he says that innate traits are only part of the cause. But the rest of his essay implies they are the primary cause. The weight [of the research on the matter](http://emilkirkegaard.dk/en/wp-content/uploads/Men-and-things-women-and-people-A-meta-analysis-of-sex-differences-in-interests.pdf http://emilkirkegaard.dk/en/wp-content/uploads/Men-and-thing...) (a significant amount of it) indicates that interests are a primary driver in the discrepancy: Therefore, from the inter-individual perspective,the individuals who pursue STEM careers are more likely to be male than female. For example, assuming that individuals within the highest 25% of a population interest distribution are likely to make occupational choices consistent with an interest type, the number of women entering the engineering occupation, then, is only 19.5% of the number of men entering the field. This percentage is very similar to the actual female–male ratio of individuals employed in engineering. In science and mathematics interest distributions, the female–male ratios in the upper 25% asymptote are 0.60 and 0.64, respectively. However, the actual female–male ratio of individuals employed in the field of physical sciences is only about 0.40 and, in mathematics, it is about 0.45. This discrepancy between interest data and real employment composition indicates that there may be reasons other than sex differences in interests that can account for gender disparity in science and mathematics. A few observations though: 1) Google tends to pull a lot from Science and Math, not just engineering, in the "tech world". Dalmore is one such individual. This indicates the ratio should be much more skewed to an even makeup. 2) Even without that Google is still pretty "male" compared to what the research indicates. 3) Research on interests is largely still post social, so we don't really have a good feeling for the biological vs social components that drive the interest rates we see today. We know some pre-social effects exist, but we don't really have a good grasp on the magnitude of such effects. His memo fails to make this differentiation.

zbobet2012 9y ago

His memo absolutely fails to mention the biases women deal with on a daily bases. It fails to mention how unjust such things can be and how they must make his female colleagues feel. And that such things are well supported by research. That failure makes his audience significantly less receptive, and puts them on the immediate defense. He should spend some serious time reading "Difficult Conversations" and other books of it's ilk. As much as he wants to avoid feelings, feelings always matter. Hence the justified accusation of his memo being "tonedef". And you are not considering the context in which it was written, or are missing key statements like: > For the rest of this document, I’ll concentrate on the extreme stance that all differences in outcome are due to differential treatment and the authoritarian element that’s required to actually discriminate to create equal representation. For him it is clearly table stakes that women are discriminated against. He doesn't feel the need to argue it because he, and the Google culture which he is addressing, finds it so imminently obvious. Something he states. Multiple times. Throughout the document. > Sure, he says that innate traits are only part of the cause. But the rest of his essay implies they are the primary cause. The weight [of the research on the matter](http://emilkirkegaard.dk/en/wp-content/uploads/Men-and-things-women-and-people-A-meta-analysis-of-sex-differences-in-interests.pdf http://emilkirkegaard.dk/en/wp-content/uploads/Men-and-thing...) (a significant amount of it) indicates that interests are a primary driver in the discrepancy: Therefore, from the inter-individual perspective,the individuals who pursue STEM careers are more likely to be male than female. For example, assuming that individuals within the highest 25% of a population interest distribution are likely to make occupational choices consistent with an interest type, the number of women entering the engineering occupation, then, is only 19.5% of the number of men entering the field. This percentage is very similar to the actual female–male ratio of individuals employed in engineering. In science and mathematics interest distributions, the female–male ratios in the upper 25% asymptote are 0.60 and 0.64, respectively. However, the actual female–male ratio of individuals employed in the field of physical sciences is only about 0.40 and, in mathematics, it is about 0.45. This discrepancy between interest data and real employment composition indicates that there may be reasons other than sex differences in interests that can account for gender disparity in science and mathematics. A few observations though: 1) Google tends to pull a lot from Science and Math, not just engineering, in the "tech world". Dalmore is one such individual. This indicates the ratio should be much more skewed to an even makeup. 2) Even without that Google is still pretty "male" compared to what the research indicates. 3) Research on interests is largely still post social, so we don't really have a good feeling for the biological vs social components that drive the interest rates we see today. We know some pre-social effects exist, but we don't really have a good grasp on the magnitude of such effects. His memo fails to make this differentiation.