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I've been slowly working through this book, it's fairly light but still a bit dense for my foggy hard-science-oriented brain.
Basically it's about demolishing gender essentialist pseudoscience.
The first part is a whole bunch of examples of how amazingly easy it is to affect people's decisions and abilities by "priming" them with stereotypes, either by putting stereotypes into their heads or just by reminding them of the stereotypes they've already been exposed to. Just putting a gender tickbox at the start of a maths test lowers women's scores, since they go "That's right, I am a woman. Women are bad at maths." (And thinking "I AM NOT BAD AT MATHS DAMMIT" still takes up valuable mental energy that could be spent calculating) And of course there's all the examples of exactly the same resume being judged differently depending on the gender/race etc associated with the name attached. People THINK they're being objective but really aren't, and will come up with complicated justifications for why their choice is logical, eg if you swap the "male" and "female" names on a pair of different resumes suddenly the traits that were unsuitable for the job when they belonged to a woman make a man the perfect choice.
She also demolishes some of the specific claims of Bad Gender Science, like "girl babies look longer at faces therefore women are naturally more intuitive therefore men are better at hard sciences" and so on (and of course as gender roles change the arguments have to twist themselves into stuff like "Women are attracted to forensic pathology and microbial biology because they...like faces and people")
Overall I'm finding it really informative but I am annoyed by how it assumes the reader is a cis het woman living in Australia/the US etc who is probably going to get married and have babies. She does acknowledge trans people, intersex people, same sex relationships, people from other cultures etc but mainly for what they can teach us about heterosexual cis etc people rather than as examples of everyday people who have to deal with gender stereotypes themselves. And, ok, most of her arguments are statistical and so the "average" woman is what matters, but she could still do better on being inclusive and intersectional. She does mention assumptions about race every now and then, but not in a very meaty way.
I'm onto part two now and she seems to be implying that there is some evidence for men and women (and male and female primates in general) being biologically hardwired differently in one particular way: men care about fitting into the male gender norms of the culture they've been brought up in whatever those norms happen to be and the same goes for women(*). The nice thing about this theory is that it says that specific gender roles are socially defined rather than innate, but that gender identities and divisions themselves are hardwired enough to debunk radfem etc dismissal of the trans experience.
(Second post)
(*)Non binary gendered people seem to be entirely off her radar, though being a small and poorly defined/understood group I guess it would be hard to come to many useful conclusions right now.
Basically it's about demolishing gender essentialist pseudoscience.
The first part is a whole bunch of examples of how amazingly easy it is to affect people's decisions and abilities by "priming" them with stereotypes, either by putting stereotypes into their heads or just by reminding them of the stereotypes they've already been exposed to. Just putting a gender tickbox at the start of a maths test lowers women's scores, since they go "That's right, I am a woman. Women are bad at maths." (And thinking "I AM NOT BAD AT MATHS DAMMIT" still takes up valuable mental energy that could be spent calculating) And of course there's all the examples of exactly the same resume being judged differently depending on the gender/race etc associated with the name attached. People THINK they're being objective but really aren't, and will come up with complicated justifications for why their choice is logical, eg if you swap the "male" and "female" names on a pair of different resumes suddenly the traits that were unsuitable for the job when they belonged to a woman make a man the perfect choice.
She also demolishes some of the specific claims of Bad Gender Science, like "girl babies look longer at faces therefore women are naturally more intuitive therefore men are better at hard sciences" and so on (and of course as gender roles change the arguments have to twist themselves into stuff like "Women are attracted to forensic pathology and microbial biology because they...like faces and people")
Overall I'm finding it really informative but I am annoyed by how it assumes the reader is a cis het woman living in Australia/the US etc who is probably going to get married and have babies. She does acknowledge trans people, intersex people, same sex relationships, people from other cultures etc but mainly for what they can teach us about heterosexual cis etc people rather than as examples of everyday people who have to deal with gender stereotypes themselves. And, ok, most of her arguments are statistical and so the "average" woman is what matters, but she could still do better on being inclusive and intersectional. She does mention assumptions about race every now and then, but not in a very meaty way.
I'm onto part two now and she seems to be implying that there is some evidence for men and women (and male and female primates in general) being biologically hardwired differently in one particular way: men care about fitting into the male gender norms of the culture they've been brought up in whatever those norms happen to be and the same goes for women(*). The nice thing about this theory is that it says that specific gender roles are socially defined rather than innate, but that gender identities and divisions themselves are hardwired enough to debunk radfem etc dismissal of the trans experience.
(Second post)
(*)Non binary gendered people seem to be entirely off her radar, though being a small and poorly defined/understood group I guess it would be hard to come to many useful conclusions right now.
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I think your review was what got me to read the book, so thanks! It probably made me notice the narrow focus a little sooner, too.
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I was so fucking pissed when I took a 600-level math course, and suddenly, out of nowhere, my brain was chattering about how even though I'd never ever had any problem ever with math before, this was the point when "women are bad at math" was gonna kick in.
And of course I was the only woman in the class, and the professor was a misogynistic asshole who kept making jokes about women, and inviting us all to laugh at said jokes, and then belatedly remembering OOPS SHIT WOMAN IN THE ROOM! and turning to stare at me in surprised horror and thus leading the entire fucking rest of the class to turn and stare at me in surprised horror, too. Because WOMAN. IN THE ROOM. WHAT IS SHE DOING HERE?
Also, the math seminars? When I would show up -- again, the only woman -- the person welcoming everyone couldn't figure out what the proper mode of address was for two dozen men and one woman, and kept botching it and botching it and botching it, thereby emphasizing that there was A WOMAN IN THE ROOM AND THAT IS WEIRD.
And I would be livid, and trying not to be livid, and pretending my damnedest to not notice and be cool, and my brain was chattering about WOMEN ARE BAD AT MATH, and I would be yelling at my brain SHUT UP SHUT UP NOT TRUE, and it was a fucking miserable quarter.
I got my A, damnit. Because not getting it WASN'T GOING TO HAPPEN. But when I say miserable quarter, I mean miserable quarter.
...*cough*...
In short, um, yes, stereotype threat. I have, in fact, heard of that, perhaps.
And here you were just trying to write a nice book review, sorry.
:: She does acknowledge trans people, intersex people, same sex relationships, people from other cultures etc but mainly for what they can teach us about heterosexual cis etc people rather than as examples of everyday people who have to deal with gender stereotypes themselves. ::
Thank you. Because yes.
:: most of her arguments are statistical and so the "average" woman is what matters, ::
You're more generous than I would have been. Averages don't tell you much at all. Distributions, however, are hella informative.
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The sexism I've encountered has been similarly subtle. I'm pretty sure the only times I've been the only girl in a maths class the class had 2-3 people total, but there was still a blokey, sometimes sleazy vibe in the maths department that made me feel ill at ease, and people are always surprised when I turn out to be good at maths because I don't seem the type somehow.
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