The Gender Data Gap


One of the books on my summer reading list was “The Moment of Lift” by Melinda Gates, the co-founder of the Bill and Melinda Gates foundation and overall awesome human being, in which she describes how empowering women and girls can help lift entire villages out of poverty. Each chapter focuses on one area in which women are disadvantaged, explains the dimensions of the inequality and the work the foundation has done to overcome these barriers alongside personal anecdotes and thoughts. It’s a great book because it shines a light on many successful and thoughtful programs all over the world that have achieved progress in traditional societies but at the same time, it shows where problems prevail. In the end, the reader feels angry and sad about the persistent prejudices faced by women and girls around the world, but you know not everything is lost because there are things we can do to improve this situation for future generations.  
One important theme throughout the book and something Melinda Gates also mentioned in this years’ Annual Letter (surprise number 4) is the gender data gap. Recently, you might have heard more about this phenomenon with the success of “Invisible Women” a book by Caroline Criado Perez in which she demonstrates how the world has been created for men given that there is by far not enough data on women. She shows how favoring the status quo based on the “male” data has disadvantaged women in our society, whether it’s that smartphones always feel too large for our hands, or long queues in front of the women’s bathroom. While these structures limit the success of women in societies that have otherwise already improved (but not achieved) equality in many areas, the gender data gap can slow down progress in development work. Treating data as gender neutral can assist the prevalence of inequalities based on gender. For example, how can we evaluate the success of a program on increasing enrolment in primary education if we don’t even ask for the different effects on boys and girls? On the surface, a program might look successful because enrolment increased, but what if the majority of the beneficiaries of this program were boys? Don’t get me wrong, education is important for every child, but it is important to understand why parents might decide to send their sons to school over their daughters. Persisting gender stereotypes keep girls out of school and in the household where their opportunities for a future outside the home are limited.
Melinda Gates’ book shows how the lack of data impedes women on girls on the individual level but at the same time how this has meaningful consequences for development work and the effectiveness of programs. Especially in agriculture, researchers have traditionally spoken to men about their needs and preferences for support but these same researches were oblivious to the fact that the majority of people working in the fields were women and hence more knowledgeable about what works what does not.
Attaining progress is complicated especially in intricate and complex areas such as gender inequality but first, we need to know what the problem looks like. Improving the gender data gap will help identify areas that need more work and determine which programs are effective at reducing inequality.

Data2X, for example, is working on this.

Also, check out a post by the Bill and Melinda Gates foundation about this topic here.


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