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Leading Global Organizations Invest in Community-Level Data to Advance Gender Equality

March 8, 2021

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Machine learning delivers long-desired insights

WASHINGTON, March 8, 2021 /PRNewswire/ — In honor of International Women’s Day and the upcoming Gender Equality Forum, technology company Fraym is releasing findings from two initiatives that used cutting-edge data and AI/ML models to better understand complex issues central to gender equality. For both projects, one funded by a grant from the Bill & Melinda Gates Foundation and the other a pilot program with Facebook’s Project 17, ML-generated data addressed a pre-existing knowledge gap and delivered critical sub-national insights.

Bill & Melinda Gates Foundation Grant

Globally, there are more than 650 million women and girls that were wed as children. Two years ago, the global community made a clear call for localized data to help map and understand this massive barrier to gender equality across the world. Fraym responded to this call and has partnered with leading actors like UNICEF, Girls Not Brides, and the Population Council as part of a Gates Foundation supported learning consortium. Through the initiative, Fraym: (1) estimated and mapped child marriage prevalence down to the 1km2 level across time and space; (2) analyzed community contexts; and (3) explored whether and how several risk factors might be associated with higher child marriage prevalence. This was done for seven countries. Access detailed findings and the complete reports to help your organization.

Facebook

In collaboration with Facebook’s Project 17, Fraym explored the use of the Facebook Survey on Gender Equality at Home and high-resolution population data to test the hypothesis that spatial gender disparities exist—and that they are not being captured by traditional data collection and analysis methods. To do this, Fraym analysts reviewed a database of over 100 spatially precise community level indicators produced from secondary data sources like the Demographic and Health Survey (DHS) to identify the most comparable measure of food security that could be sex-disaggregated and selected child undernutrition to weight Facebook’s national statistics on food security. The findings unearthed subnational differences in male and female food security in Nigeria, and can be used to consider how we measure outcomes in the future. View the hotspot maps and read the full brief.

About Facebook’s Project 17

Project 17 is Facebook’s partnerships-first approach to accelerating progress on the Sustainable Development Goals (SDGs). Its current area of focus is increasing the availability and use of gender data.

About Fraym

Fraym uses advanced machine-learning to generate insights on communities around the globe. The company’s location-based data about population characteristics and behaviors is employed by governments and organizations tackling some of the world’s most pressing challenges like inequity and insecurity, climate impact and vulnerability, and pandemic preparedness and response. Using proprietary algorithms, Fraym produces datasets that cover a wide range of indicators including socio-economics, attitudes, media consumption, health, education, and access to services for places with data gaps. Their geospatial data and analysis is available for 100+ countries at one square kilometer resolution—even in remote areas.

Fraym.io | info@fraym.io  | 202.869.0878

Media Contact
Rachael Mandell
Director of Marketing & Communications at Fraym
R.Mandell@fraym.io

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