The Wells-Du Bois Protocol for Machine Learning Bias: Building Critical Quantitative Foundations for Third Sector Scholarship

This paper charts the rapid rise of data science methodologies in manuscripts published in top journals for third sector scholarship, indicating their growing importance to research in the field. We draw on critical quantitative theory (QuantCrit) to challenge the assumed neutrality of data science...

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Veröffentlicht in:	Voluntas (Manchester, England) England), 2023-02, Vol.34 (1), p.170-184
Hauptverfasser:	Monroe-White, Thema, Lecy, Jesse
Format:	Artikel
Sprache:	eng
Schlagworte:	Bias Data science Machine learning Marginality Minority groups Misrepresentation Mitigation Neutrality Political Science Race Research Papers Social Policy Social Sciences
Online-Zugang:	Volltext
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