CONCEPTS OF CULTURE‐FAIRNESS
Abstract
Fairness of a test relates to fair use. One definition of fair use states that a common qualifying score may be used with two groups if the regression line based on one group does not systematically over‐ or under‐predict criterion performance in the other. However, it is shown that when the two groups differ appreciably in mean test score, the above procedure, which is “fair” to individual members of the group scoring lower on the test, is “unfair” to the lower group as a whole in the sense that the proportion qualified on the test will be smaller, relative to the higher‐scoring group, than the proportion that will reach any specified level of criterion performance. An alternate definition would specify that the qualifying scores on a test should be set at levels that will qualify applicants in the two groups in proportion to the fraction of the two groups reaching a specified level of criterion performance.
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The general notions from early fairness literature transfer to (binary) classification settings and define essential concepts such as protected/demographic variables, notions of group vs individual fairness, impossibility conditions between fairness conditions, and metric-based fairness quantification.
“However, the general notions transfer to (binary) classiication settings and thus deine essential concepts such as protected/demographic variables (e.g.[72,73]), notions of group vs individual fairness (e.g.[257,278]), impossibility conditions between fairness conditions ( [81]), and metric-based fairness quantiication (e.g., true positive rates, [74]).”
From Fairness in machine learning: A survey (2024) · cites this paper as [278]
Cites
TEST BIAS: PREDICTION OF GRADES OF NEGRO AND WHITE STUDENTS IN INTEGRATED COLLEGES
Cleary, T. A. (1968) · Journal of Educational Measurement · doi:10.1111/j.1745-3984.1968.tb00613.x · Cited by 658 · see citing works
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Algorithmic Fairness: Choices, Assumptions, and Definitions
Mitchell, S., Potash, E., Barocas, S., D'Amour, A., & Lum, K. (2021) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-042720-125902 · Cited by 687 · see citing works
Fairness in machine learning: A survey
Caton, S., & Haas, C. (2024) · ACM Computing Surveys · doi:10.1145/3616865 · Cited by 646 · see citing works
50 Years of Test (Un)fairness: Lessons for Machine Learning
Hutchinson, B., & Mitchell, M. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency · doi:10.1145/3287560.3287600 · Cited by 297 · see citing works
Sackett, P. R., Borneman, M. J., & Connelly, B. S. (2008) · American Psychologist · doi:10.1037/0003-066x.63.4.215 · Cited by 233 · see citing works
ANOTHER LOOK AT “CULTURAL FAIRNESS”<sup>1</sup>
DARLINGTON, R. B. (1971) · Journal of Educational Measurement · doi:10.1111/j.1745-3984.1971.tb00908.x · Cited by 199 · see citing works
Fairness in Machine Learning: A Survey
Caton, S., & Haas, C. (2020) · arXiv · doi:10.48550/arxiv.2010.04053 · Cited by 646 · see citing works
UTILITIES AND THE ISSUE OF FAIRNESS IN A DECISION THEORETIC MODEL FOR SELECTION
SAWYER, R. L., COLE, N. S., & COLE, J. W. L. (1976) · Journal of Educational Measurement · doi:10.1111/j.1745-3984.1976.tb00182.x · Cited by 47 · see citing works
Antidiscrimination Insurance Pricing: Regulations, Fairness Criteria, and Models
Xin, X., & Huang, F. (2024) · North American Actuarial Journal · doi:10.1080/10920277.2023.2190528 · Cited by 43 · see citing works
“As early as the 1970s, research in other fields noted the conflict between individual fairness and group fairness; see Thorndike (1971) and Sawyer, Cole, and Cole (1976).”
BackgroundReeb, M. (1976) · Journal of Applied Psychology · doi:10.1037//0021-9010.61.3.253 · Cited by 10 · see citing works
- Authors
- THORNDIKE, R. L.
- Affiliations
- Columbia University (US)
- Corresponding author
- THORNDIKE, ROBERT L.
- Venue
- Journal of Educational Measurement
- Publisher
- Wiley
- Published
- 1971-06
- Volume
- 8
- Issue
- 2
- Pages
- 63-70
- ISSN
- 0022-0655 (ISSN-L)
- 1745-3984
- OpenAlex
- W2086406824
- Cited by
- 265
- References
- 1
- Citations by year
- 2026: 5 · 2025: 1 · 2024: 1 · 2023: 7 · 2022: 6 · 2021: 5 · 2020: 5 · 2019: 6 · 2018: 3 · 2017: 2 · 2016: 1 · 2015: 3 · 2014: 3 · 2013: 4 · 2012: 1
- FWCI
- 22.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Educational Measurement (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Education › Educational Assessment and Pedagogy
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical Education and Admissions
- Keywords
- test fairness, regression line
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