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Why better data is crucial for gender equality

A lack of data about the lives of women and girls means that policy-makers are forming decisions without full information about realities. To make amends we need to close the gender data gap.

Most people are aware of the “gender gap” that negatively a ffects women with regards to, for example, pay, promotion and access to services. More unfamiliar, but just as alarming, is the “gender data gap.” This is, in e ffect, gender inequality in the world of information gathering — such as sampling and surveys — which, accidentally or intentionally, neglects to recognise the real lives and experiences of women and girls.

That’s a big problem says Emily Courey Pryor, Executive Director of Data2X, a collaborative technical and advocacy platform dedicated to improving the quality, availability, and use of gender data. Because, if government policymakers base important decisions on insights from incomplete or gender-biased infor-mation, women are invariably going to get a raw deal.

Better data means female empowerment

“Take the economic data government policymakers use, which often does not count unpaid work,” says Pryor. “This is work typically done by women and includes caring for children or elderly parents or helping in the family business. Yet, because it’s unpaid it’s also unseen — which means the value of women’s economic contributions often go unrecognised. As a result, policies can be made that don’t reflect their needs or respond to their concerns.”

Because unpaid work is also ‘unseen’ — it means the value of women’s economic contributions often go unrecognised.

“We know that good gender data is essential to drive policies that promote gender equality”, notes Pryor. “But right now, policymakers around the world only have access to biased or incomplete data that does not accurately reflect the lives of women and girls,” she says.

Of course, admitting you have a problem is one thing. Doing something about it is quite another. “Closing the gender data gap requires deeper understanding from the statisticians and data scientists who create data methodologies and surveys, to the technicians who build machine learning algorithms,” says Pryor. “Everyone needs to ensure that everything they design is able to capture data that truly reflects women’s real, lived experiences. That needs proper human resourcing, financial resourcing and training

Engagement needed from policy-makers

Policymakers must be actively engaged in the pursuit of gender data. “They need to be full partners in the process,” says Pryor. “They have to be completely engaged as data users, highlight why access to good data is so important and call for resourcing to ensure better data collection.

”When data is complete and unbiased, positive change can happen at policy level. Pryor points to the female senators in Colombia who fought to get a law passed which led to the country’s first ever time use survey, used to measure unpaid work like domestic tasks and caring for others. As a result, Colombia’s government has begun working on a policy to address the burden of unpaid care.

“Closing the gender data gap is not easy and takes time,” says Pryor. “But I do feel a sense of optimism — particularly when I hear examples like Colombia. Four years ago, the gender data gap was an issue known mainly to statisticians or academics. Now, there’s a new energy and interest in this from all kinds of people who care about gender equality and international development.”

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