Machine Scoring Fairness
Machine Scoring Fairness is a methodological construct in educational assessment that ensures automated scoring systems do not systematically disadvantage individuals or groups based on irrelevant attributes such as race, gender, or socioeconomic background.
6
Publications
328
Citations
14
Authors
6
Institutions
Publications per year
2017–2026
5
Variants
Algorithmic Scoring EquityAutomated Assessment Fairness
Parents
6
Investigating Human + Machine Complementarity for Recidivism Predictions
Sarah Tan, Julius Adebayo, Kori Inkpen et al. · arXiv (Cornell University) · 2018 · 27 citations · Full text
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6

University of Georgia
Athens, United States
1 h-index
1 publications
82 citations
Health Affairs
Bethesda, United States
1 h-index
1 publications
47 citations
King's College London
London, United Kingdom
1 h-index
1 publications
21 citations
Educational Testing Service
Princeton, United States
1 h-index
3 publications
417 citations
Stony Brook University
Stony Brook, United States
1 h-index
1 publications
82 citations

Goldsmiths University of London
London, United Kingdom
1 h-index
1 publications
21 citations

University of Salford
Salford, United Kingdom
1 publications
12 citations

Bournemouth University
Poole, United Kingdom
1 publications
12 citations
1–8 of 6
1 publications · 47 citations
1
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1 publications · 21 citations
1
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1 publications · 139 citations
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1 publications · 82 citations
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Repository · 1 publications · 27 citations
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