Equal Opportunity

Equal Opportunity is a fairness criterion in machine learning that requires a classifier to have equal true positive rates across different demographic groups, ensuring that members from all groups have the same likelihood of being correctly identified as positive when they are indeed positive.

1.1K

Publications

73.7K

Citations

1.8K

Authors

782

Institutions

Publications per year

2017–2026

163

Authors

1.8K

  1. JE
    John E. Roemer

    Yale University, United States

    8 publications · 645 citations

    8

    h-index

  2. GS
    Glenda Strachan

    Griffith University, Australia

    5 publications · 224 citations

    5

    h-index

  3. RJ
    Richard J. Arneson

    University of California San Diego, United States

    5 publications · 2.5K citations

    5

    h-index

  4. KR
    Kenneth R. Howe

    University of Colorado Boulder, United States

    5 publications · 281 citations

    5

    h-index

  5. VP
    Vito Peragine

    University of Bari Aldo Moro, Italy

    5 publications · 461 citations

    5

    h-index

1–5 of 1.8K

Venues

  1. Choice Reviews Online

    CRO · 27 publications · 6.1K citations

    22

    h-index

  2. SSRN Electronic Journal

    Repository · 22 publications · 1.7K citations

    15

    h-index

  3. Women in Management Review

    13 publications · 587 citations

    12

    h-index

  4. The Journal of Negro Education

    11 publications · 567 citations

    11

    h-index

  5. Gender Work and Organization

    10 publications · 390 citations

    10

    h-index

1–5