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Leveraging Data for Gender Equality

Data Feminism Network

Leading a cultural movement toward equitable and gender-sensitive data practices.

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The fight for gender equality is the fight against all forms of oppression.

Data is a form of power for those who have the resources to collect and analyze it.

Encoded human prejudice and bias in data can amplify forms of discrimination that have limited certain groups for generations. While data shows great promise, it can further embed unequal distributions of power that subordinate minoritized groups.

Bias in data perpetuates inequalities, such as through hiring processes, medical care, and criminal justice systems.

Our Mission

Our mission is to promote equitable and gender-sensitive data systems for better, more inclusive decision making.

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We work to cultivate a society where everyone benefits equitably from data and technology
FREE Study Guides

Eager to read these rad data feminist books? Our FREE study guides can serve as a supporting resource to help you absorb key themes and concepts.

Invisible Women 
Study Guide
Race After Technology
Study Guide
Data Feminism 
Study Guide
Weapons of Math Destruction
Study Guide
Algorithms of Oppression 
Study Guide
Automating Inequality
Study Guide
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Data collection, femicides and policy change: Lessons from Mexico

Brenda González Córdova, Grants Manager at DFN, shares how a private citizen in Mexico initiated policy change to make women safer through contextualized data collection of feminicides.

"Data Feminism is a way of thinking about data that’s informed by direct experience, commitment to action, and intersectional feminist thought." 

- Catherine D’Ignazio & Lauren F. Klein, 

Data Feminism

"The truth is that around the world, women continue to be disadvantaged by a working culture that is based on the ideological belief that male needs are universal."

- Caroline Criado-Perez, Invisible Women: Data Bias in a World Designed for Men

"If advocacy for women and girls is about giving voice to the voiceless – gathering and analyzing data is about making the invisible visible."

- Melinda Gates,

Bill and Melinda Gates Foundation

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