Not a “data type”? There’s room for you in the gender data movement.

Karolina Ramos July 17, 2019

It’s been a few weeks since the World Cup, and I’m still riding the high of the U.S. Women’s National soccer team’s win.

I’m “liking” every post about Megan Rapinoe. I grab drinks with friends, ostensibly in the team’s honor. We entertain and then swiftly abandon the idea of joining a pick-up soccer league. And amidst the celebrations and revelry are the numbers:

  • $4 million: the U.S. Women’s team’s collective net earnings for their World Cup victory.
  • 10.5%: the portion of net earnings the women’s team received compared to the winning men’s team for the same achievement.
  • Four: the number of World Cup championship titles under the U.S. women’s team belt. The U.S. men’s team have yet to claim the same win.
Credit: Alex Grimm/Ghetty Images

We often think of gender data as firmly technical. Sex-disaggregated data, gender statistics, indicators—these terms and concepts live in UN chambers, in conference rooms with labor statisticians seated around the table, in annual reports and indices. But really, gender data is part of common conversation.

It emerges in my texts with friends when we encourage each other to ask for raises in a small effort to combat the gender pay gap.

It pops up as young women consider runs for office, inspired by a tide of women entering Congress; we wonder how many women around the world are already leading the charge, but there’s no international baseline for data collection on women in local office.

And it makes its way into sports bars, as fans watch their beloved soccer team dominate the field again and again, showing exactly what they’re worth.

To be clear, I’m not trying to impose an agenda into every conversation. But I often don’t have to: the gender elements impose themselves, and within them, data aspects emerge, too. Gender data may be a technical topic, but it’s one with widespread relevance even to those who don’t consider themselves “data types”. I should know, because I’m one of them.

Karolina Ramos

I came to Data2X three years ago with little quantitative background but an appetite to understand how data informs gender equality efforts and global policymaking. I didn’t aspire to become a technical expert overnight, but I did want to develop a basic command of the language of the data world.

As I prepare to transition from Data2X to a graduate program in public policy this fall, these considerations still motivate me:

  • What role do policymakers play in driving demand for representative data?
  • How do we measure the impact of policies, and on whom?
  • Does the information that makes its way to the desks of officials, from municipal employees to UN staff, capture the diversity of needs and interests of a given community?

At the crux of these questions is one that drove me to Data2X and drives me still: how can we possibly understand women’s needs and realities if we don’t collect information on them in the first place?

Data2X calls for gender mainstreaming statistical systems so we collect and use data on women and girls from the onset. But what does this agenda mean for me and my fellow “non-technical” types, the ones who dreaded college statistics but care deeply about equity and the information which drives it to fruition; the ones who want to grasp the numbers behind women’s health outcomes; or the variables that determine female athletes’ paychecks?

It means we cannot assume that representativeness in data is a given: we have to ask who is and isn’t counted. It means we cannot assume that there is demand for representative data: we have to use our influence and platforms to call for it.

Perhaps most importantly, it means we can’t assume that “technical types” and “advocates” cannot be one in the same.

Some of the most compelling gender equality champions can be those who have spent years steeped in data networks, and some of the most pressing questions about how to make statistical systems more gender-responsive can come from civil society activists.

While I’ll never claim to be an expert on the intricacies of survey methodology or data financing, I can claim to always be striving towards informed, data-driven advocacy and policymaking. Because there’s room for both “types” at the table—or at the bar for a celebratory round.

Karolina Ramos worked for Data2X from 2016 – 2019.

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