Overview:
Those who make decisions, design policies around their needs. Creating a data gap about needs not their own. That is what happens to women. As men cannot relate to female experiences or have those personal experiences, they do not think about women’s needs. Not a deliberate or malicious exclusion. Men just do not think about women’s different needs, which includes biological and social needs. This is the gender data gap, developed through the absent presence of women. The silences have negative consequences on women’s daily life. To rectify this data gap, to understand women and the female experience, all that is needed is to ask women.

Valuable insights can be gained by including women in the production of knowledge, because they have different experiences. Although women make up half the population, the female experience is niche. The male experience and perspective is seen as universal. The word man has become a reference to the human species. Using the default male identity, many tools, medicines, and infrastructure have been designed using male averages. The standard for human representation. But women have different body shapes, chemistry, and use of infrastructure. This difference has caused many women to be hurt by these designs. The problem is the social meaning of the female body, not the female body itself.

Data and Gender:
Without considering the accounts and experiences of women, historical facts become distorted to convey half-truths. The myths told affect how society sees itself. Misunderstanding the data has negative consequences.

Sex and gender are not the same, but are interrelated. Sex is the biological characteristics. Gender is a social meaning to the biological characteristics.

Role models ted to be those who look like the individual. While women tend to accept men as role models, men do not see women as role models.

Sexual harassment is not report for various reasons such as social, not knowing what counts as sexual harassment, the response from authorities, and not knowing what to do is something does happen. Having a misogynistic culture prevent women from entering professions, rather than their lack of ability and want.

Women and the Economy:
Women tend to do most of the invisible work. Work that needs to be done, but is not paid. Such as cooking, cleaning, and child care. Men don’t tend to consider the invisible work done around men. That unpaid work enables the men to go to paid work.

Women’s unpaid work benefits society as a whole. When governments cut public services, demand for the services does not cease. The work is transferred to women, reducing their labor-participation rates, and GDP. As unpaid work does not count in GDP, making a lot of productive effort to go uncounted for. Need to start collecting data on who is impacted by the programs.

The gig economy has created ways to get around employers providing basic employee rights. The workers have less rights to begin with, making harder for the workers to ask for more.

Blind auditions are a tool used to prevent the people hiring from seeing whose auditioning or interviewing. This process was used to get many more women into the New York philharmonic. The blind audition made the process meritocratic.

Meritocracy is usually a myth, but people believe it to be true even when reality does not fit. A belief in meritocracy tend to make people biased against it. Believing oneself as meritocratic, or as not sexist, makes people behave in ways that is less meritocratic, or sexist.

Caveats?
The book is mostly about the negative consequences of the gender data gap. Not much positive values of rectifying the data gap, showing the benefits of women’s experience. The gender data gap is not new, with a variety of books which include data and information on women and other often marginalized groups. There have been cultures and books that features women prominently. By ignoring the data of these corrections of the data gaps, creates another data gap with the associated misrepresentations.

Differences between women and men is expressed, but not the similarities. There are activities and physical features that are similar, but they are not mentioned. Advantages of men is expressed, but not the advantages of women.

It was mentioned that asking women is a tactic that can remove the gender data gap. The problem is that depending on the culture, asking women about women’s views and experiences can cause negative repercussions. As the men can become stigmatized for asking about those different views.

What is limited is an account of how redesigning everything to incorporate the gender difference would be like. How society would function, and the female/male institutions would look like. Historically, the reason for the uniform beliefs and implementations within institutions is that they are cheaper, as diverse changes are often too expensive. This book shows that there is a lot of value added by women, but that would require change. ( )

It was incredibly repetitive about the point that women (though she has yet to mention anything about trans people) have been left out of consideration in pretty much all areas of society and science. Important, but I don't think it necessarily needed to be a full length book.

Stopped at 69%

This book was enlightening for me. I kind of knew that science has made male the default and female the exceptional case, but to see myriad examples and their negative consequences is just mind boggling. It may not cover intersectional demographics but that’s probably a whole other book on its own, and a far more depressing book at that. If you’re a scientist, you must read it and internalize the importance of not making any one demographic group the default to which all other groups must generalize. ( )

How are we so bad at intersectional feminism still. The information in here is not surprising if you're a woman, even if it's infuriating. What's more infuriating is the way trans and nonbinary people are completely ignored. You'd think we'd learn our lesson being excluded from so many aspects of the world that we shouldn't be excluding anyone else, but that's not the case here sadly. ( )

Quite a masterpiece. Abundance of clear examples to prove the hypothesis. Makes you open your eyes in everyday situations.
Though, on several instances correlation seems to be mixed up with causation. ( )