Why is gender-disaggregated data important? How are women discriminated against at a government level?
Gender-disaggregated data is simply data that is separated by gender, but it’s extremely important. If the government collects gender-specific data, we can improve women’s standing in society.
Check out the importance of gender-disaggregated data below.
How the Gender Data Gap Affects Women at the Governmental Level
In Invisible Women, Caroline Criado Perez argues that even when we do collect data on women, we still have a male-as-default mindset that ultimately harms women. Solving this issue emphasizes the importance of gender-disaggregated data.
Perez specifically contends that due to our male-as-default mindset, we collect data on people and assume that it represents the average life experience. However, women have gender-specific concerns. By not collecting and using gender-disaggregated data we create systems that ultimately discriminate against women.
(Shortform note: Experts suggest that if we did collect and use gender-disaggregated data, we could create systems that not only don’t discriminate against women but also actively improve their standing in society. These experts divide governmental policies into categories ranging from “gender-unaware,” which don’t acknowledge how decisions affect each gender differently, to “gender-transformative,” which seek to combat discriminatory practices against women so they become more equal to men. For example, a gender-transformative policy might try to reduce women’s care responsibilities.)
Perez points to how modern governments that don’t use gender-disaggregated data to analyze their budgets spend and save money. These governments often try to foster economic growth by cutting taxes on their highest earners. However, almost every country has a gender pay gap: Globally, men earn nearly 38% more than women. Since high earners are more likely to be men, these tax cuts are more likely to benefit men—not women. Therefore Perez argues that by not gender-analyzing their taxation systems, modern governments pass tax policies that disproportionately benefit men and thus discriminate against women.
Moreover, Perez argues that when these governments need to save money, their failure to consider how policy changes might impact men and women differently results in policies that disproportionately disadvantage women. Thus, the refusal to use gender-disaggregated data discriminates against them. Notably, governments often try to save money by closing public services—a move that, according to Perez, disproportionately affects women.
Why is this so? The public services the government closes often provide care work: After the 2008 financial crisis, the UK cut funding for nearly 300 children’s centers. But even if the government doesn’t provide this care, someone still has to. And usually, that burden is passed onto women, who do 75% of the world’s unpaid care work. However, as Perez notes, doing unpaid labor takes time away from a woman’s ability to do paid labor—and therefore, the closure of these public services often causes women to lose potential income.
(Shortform note: During the Covid-19 pandemic, governments were forced to close public services for health reasons. In the UK, several children’s centers provided solely virtual services during lockdowns. So when these services closed, who provided the unpaid care and potentially lost income as a result? One study found that the results varied significantly by country, even if these countries were close to each other, had the same number of Covid-19 cases, and were of similar size. In the UK, men took on a greater share of the childcare. But in Germany, the number of partnered women providing all of the childcare increased.)
In this way, the government’s failure to review gender-disaggregated data—in other words, a gender data gap caused by a male-as-default mindset—results in the creation of budgets and taxation systems that ultimately harm women’s economic standing.
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Like what you just read? Read the rest of the world's best book summary and analysis of Caroline Criado Perez's "Invisible Women" at Shortform .
Here's what you'll find in our full Invisible Women summary :
- How society's male-as-default mindset leads to a gender data gap
- Why cars don't properly protect women during accidents
- Why we don’t know how most medicines affect women