Invisible Women : Exposing Data Bias in a World Designed for Men

[F]emales aren’t even included in animal studies on female-prevalent diseases. Women are 70% more likely to suffer depression than men, for instance, but animal studies on brain disorders are five times as likely to be done on male animals. A 2014 paper found that of studies on female-prevalent diseases that specified sex (44%), only 12% studied female animals.

Alongside insisting that sex differences don’t matter, some researchers advocate against the inclusion of women in research on the basis that while biological sex may matter, the lack of comparable data arising from the historical data gap makes including women inadvisable [..] Female bodies (both the human and animal variety) are, it is argued, too complex, too variable, too costly to be tested on. Integrating sex and gender into research is seen as ‘burdensome’.

pattern recognition sounds data-driven, but it’s basically just a fancy term for looks-similar-to-something-that-has-worked-in-the-past – where ‘something’ could be white-male-founder-who-dropped-out-of-Harvard-and-wears-hoodies

When ‘brilliance’ is considered a requirement for a job, what is really meant is ‘a penis’. [...] We just don’t see women as naturally brilliant. In fact, we seem to see femininity as inversely associated with brilliance.

[A] friend of mine got a similarly unhappy review from a male student for focusing ‘too much’ on feminism in her political philosophy lectures. She had spoken about feminism once in ten classes.

if in Silicon Valley meritocracy is a religion, its God is a white male Harvard dropout

Some call women’s segregation into low-paid work a choice. But it’s a funny kind of choice when there is no realistic option other than the children not being cared for and the housework not getting done. In any case, fifty year’s worth of US census data has proven that when women join an industry in high numbers, that industry attracts lower pay and loses ‘prestige’, suggesting that low-paid work chooses women rather than the other way around.

[M]ale universality is also a cause of the gender data gap: because women aren’t seen and aren’t remembered, because male data makes up the majority of what we know, what is male comes to be seen as universal. [...] In such a framing, women are set up to be forgettable. Ignorable. Dispensable – from culture, from history, from data.
And so, women become invisible.

Identity is a potent force that we ignore and misread at our peril [...] But misreading and ignoring identity is exactly what obfuscating maleness under the guise of gender-neutral universality causes us to do.

while there is evidence that women can to a certain extent accept men as role models, men won’t do the same for women

The result of this deeply male-dominated culture is that the male experience, the male perspective, has come to be seen as universal, while the female experience – that of half the global population, after all – is seen as, well, niche.

«Женщины, которые хорошо себя ведут, не имеют шанса войти в историю» Лорел Тэтчер Ульрих

О принадлежности к белой расе и мужскому полу молчат именно потому, что их не нужно оговаривать особо. Белая раса и мужской пол абсолютны. Они безусловны. Это настройки по умолчанию. И это очевидно для тех, чья принадлежность не «настроена по умолчанию», для тех, о чьих нуждах и мнениях обычно забывают, для всех, кто привык противостоять миру, в котором их и их потребностей как бы не существует.

Любая женщина, хоть раз побывавшая в кинотеатре, знает, что происходит, как только в зале зажигается свет: все спешат в туалет, и мгновенно и неизбежно образуется очередь, которая вскоре перегораживает фойе.

Женщины привыкли к очередям в туалет.