Data Feminism

A framework developed by Catherine D'Ignazio and Lauren Klein that applies intersectional feminist thought to the practice of working with data, offering seven principles including examining power, challenging power, elevating emotion and embodiment, rethinking binaries, embracing pluralism, considering context, and making labour visible. In accessibility research, Data Feminism provides a practical and community-reviewed guide for operationalising intersectionality—making Critical Theory accessible to practitioners outside academia and helping researchers recognise how power structures shape which experiences of disability are studied and whose needs are prioritised in technology design.