Intersectional Fairness
Intersectional Fairness is a fairness evaluation framework that extends beyond individual protected attributes by systematically accounting for the compounded disadvantages arising from the overlapping identities of marginalized groups in algorithmic systems.
17
Publications
714
Citations
48
Authors
27
Institutions
Publications per year
2017–2026
17
17
An Intersectional Definition of Fairness
James R. Foulds, Rashidul Islam, Kamrun Naher Keya et al. · 2020 · 195 citations
Computing, Data Science, Economics +14
Jenny L. Davis, Apryl Williams, Michael W. Yang · Big Data & Society · 2021 · 130 citations · Full text
Angelina Wang, V. Ramaswamy, Olga Russakovsky · 2022 ACM Conference on Fairness, Accountability, and Transparency · 2022 · 84 citations · Full text
1–5 of 17
48
3
h-index
University of Maryland, Baltimore County, United States
3 publications · 237 citations
3
h-index
University of Maryland, Baltimore County, United States
2 publications · 217 citations
2
h-index
2
h-index
1
h-index
1–5 of 48
27
University of Michigan
Ann Arbor, United States
2 h-index
5 publications
242 citations
University of Maryland, Baltimore County
Baltimore, United States
2 h-index
8 publications
868 citations
University of Illinois Chicago
Chicago, United States
2 h-index
2 publications
58 citations

University of Notre Dame
Notre Dame, United States
1 h-index
1 publications
130 citations
University of Pennsylvania
Philadelphia, United States
1 h-index
1 publications
24 citations
Oregon State University
Corvallis, United States
1 h-index
1 publications
55 citations
Shandong University of Political Science and Law
Jinan, China
1 h-index
3 publications
51 citations
Arizona State University
Tempe, United States
1 h-index
2 publications
36 citations
1–8 of 27
Repository · 5 publications · 79 citations
5
h-index
Conference · 2 publications · 139 citations
2
h-index
1 publications · 130 citations
1
h-index
Conference · 1 publications · 14 citations
1
h-index
Conference · 1 publications · 18 citations
1
h-index
1–5