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THE DIVERSITY–VALIDITY DILEMMA: STRATEGIES FOR REDUCING RACIOETHNIC AND SEX SUBGROUP DIFFERENCES AND ADVERSE IMPACT IN SELECTION
Author(s) -
PLOYHART ROBERT E.,
HOLTZ BRIAN C.
Publication year - 2008
Publication title -
personnel psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.076
H-Index - 142
eISSN - 1744-6570
pISSN - 0031-5826
DOI - 10.1111/j.1744-6570.2008.00109.x
Subject(s) - diversity (politics) , dilemma , psychology , situational ethics , subgroup analysis , social psychology , selection (genetic algorithm) , external validity , balance (ability) , applied psychology , computer science , political science , medicine , meta analysis , artificial intelligence , epistemology , law , philosophy , neuroscience
Pyburn, Ployhart, and Kravitz (this issue, 2008) introduced the diversity–validity dilemma: that some of the most valid predictors of job performance are also associated with large racioethnic and sex subgroup predictor score differences. This article examines 16 selection strategies hypothesized to minimize racioethnic and sex subgroup differences and adverse impact and, hence, balance diversity and validity. Rather than presenting a highly technical review, our purpose is to provide practitioners with a concise summary, paying particular attention to comparing and contrasting the effectiveness of the strategies and reporting new developments. The paper is organized around 4 key questions: (a) Which strategies are most effective for reducing subgroup differences? (b) Which strategies do not involve a validity tradeoff? (c) What are the major new developments in strategies for reducing adverse impact? (d) What are the major new developments in alternative predictor measurement methods (e.g., interviews, situational judgment tests, assessment centers) for reducing adverse impact? We then conclude with recommendations and caveats for how to best balance diversity and validity. These ideas are developed further in Kravitz (this issue, 2008), who considers even broader approaches for solving the diversity–validity dilemma.