Diversity shrinkage: Cross-validating Pareto-optimal weights to enhance diversity in hiring practices
Publication Type
Journal Article
Publication Date
12-2017
Abstract
To reduce adverse impact potential and improve diversity outcomes from personnel selection, one promising technique is De Corte, Lievens, and Sackett's (2007) Pareto-optimal weighting strategy. De Corte et al.'s strategy has been demonstrated on (a) a composite of cognitive and noncognitive (e.g., personality) tests (De Corte, Lievens, & Sackett, 2008) and (b) a composite of specific cognitive ability subtests (Wee, Newman, & Joseph, 2014). Both studies illustrated how Pareto-weighting (in contrast to unit weighting) could lead to substantial improvement in diversity outcomes (i.e., diversity improvement), sometimes more than doubling the number of job offers for minority applicants. The current work addresses a key limitation of the technique-the possibility of shrinkage, especially diversity shrinkage, in the Pareto-optimal solutions. Using Monte Carlo simulations, sample size and predictor combinations were varied and cross-validated Pareto-optimal solutions were obtained. Although diversity shrinkage was sizable for a composite of cognitive and noncognitive predictors when sample size was at or below 500, diversity shrinkage was typically negligible for a composite of specific cognitive subtest predictors when sample size was at least 100. Diversity shrinkage was larger when the Pareto-optimal solution suggested substantial diversity improvement. When sample size was at least 100, cross-validated Pareto-optimal weights typically outperformed unit weights-suggesting that diversity improvement is often possible, despite diversity shrinkage. Implications for Pareto-optimal weighting, adverse impact, sample size of validation studies, and optimizing the diversity-job performance tradeoff are discussed.
Keywords
Adverse impact, Cognitive ability/intelligence, Cross-validation, Diversity, Pareto-optimal weighting
Discipline
Applied Behavior Analysis | Industrial and Organizational Psychology
Research Areas
Psychology
Publication
Journal of Applied Psychology
Volume
102
Issue
12
First Page
1636
Last Page
1657
ISSN
0021-9010
Identifier
10.1037/apl0000240
Publisher
American Psychological Association
Citation
SONG, Q. Chelsea, WEE, Serena, & NEWMAN, Daniel A..(2017). Diversity shrinkage: Cross-validating Pareto-optimal weights to enhance diversity in hiring practices. Journal of Applied Psychology, 102(12), 1636-1657.
Available at: https://ink.library.smu.edu.sg/soss_research/2395
Additional URL
https://doi.org/10.1037/apl0000240