Seven intersectional feminist principles for equitable and actionable COVID-19 data
Name
2053951720942544.pdf
Size
245.85 KB
Format
Adobe PDF
Checksum (MD5)
807d017946203dc96f9a2684a07f72cf
Author(s)
D'Ignazio, Catherine S
Klein, Lauren F.
Date Issued
July 2020
Journal
Big Data & Society
Publisher
SAGE Publications
Citation
D'Ignazio, Catherine and Lauren F. Klein. "Seven intersectional feminist principles for equitable and actionable COVID-19 data." Big Data & Society 7, 2 (July 2020): dx.doi.org/10.1177/2053951720942544. © 2020 The Author(s)
Version
Final published version
Abstract
This essay offers seven intersectional feminist principles for equitable and actionable COVID-19 data, drawing from the authors' prior work on data feminism. Our book, Data Feminism (D'Ignazio and Klein, 2020), offers seven principles which suggest possible points of entry for challenging and changing power imbalances in data science. In this essay, we offer seven sets of examples, one inspired by each of our principles, for both identifying existing power imbalances with respect to the impact of the novel coronavirus and its response, and for beginning the work of change.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1177/2053951720942544
