Data Feminism

The SoundBox Collection site, like the research undertaken by the UBCO SpokenWeb team, is built with attention to the principles set out in Data Feminism by Catherine D’Ignazio and Lauren F. Klein, whose work we gratefully acknowledge:

The hardcover of Data Feminism by Catherine D’Ignazio and Lauren F. Klein photographed on Karis Shearer’s table.

1. Examine Power

Data feminism begins by analyzing how power operates in the world.

2. Challenge Power

Data feminism commits to challenging unequal power structures and working toward justice.

3. Elevate Emotion and Embodiment

Data feminism teaches us to value multiple forms of knowledge, including the knowledge that comes from people as living, feeling bodies in the world.

4. Rethink Binaries and Hierarchies

Data feminism requires us to challenge the gender binary, along with other systems of counting and classification that perpetuate oppression.

5. Embrace Pluralism

Data feminism insists that the most complete knowledge comes from synthesizing multiple perspectives, with priority given to local, Indigenous, and experiential ways of knowing.

6. Consider Context

Data feminism asserts that data are not neutral or objective. They are products of unequal social relations, and this context is essential for conducting accurate, ethical analysis.

7. Make Labour Visible

The work of data science, like all work in the world, is the work of many hands. Data feminism makes this labour visible so that it can be recognized and valued.

D’Ignazio, Catherine and Lauren F. Klein. Data Feminism. MIT Press, 2020.