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Some Comments on Pareto Thinking, Test Validity, and Adverse Impact: When ‘and’ is optimal and ‘or’ is a trade‐off
Author(s) -
Potosky Denise,
Bobko Philip,
Roth Philip L.
Publication year - 2008
Publication title -
international journal of selection and assessment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.812
H-Index - 61
eISSN - 1468-2389
pISSN - 0965-075X
DOI - 10.1111/j.1468-2389.2008.00425.x
Subject(s) - weighting , pareto principle , psychology , test (biology) , selection (genetic algorithm) , field (mathematics) , relation (database) , external validity , social psychology , applied psychology , operations management , computer science , artificial intelligence , economics , data mining , mathematics , medicine , paleontology , biology , pure mathematics , radiology
De Corte, Lievens, and Sackett add to the literature on selection test validity and adverse impact (AI). Their Pareto‐based weighting scheme essentially asks organizations if they are willing to give up some validity to hopefully achieve some reduction in AI. We considered their approach and conclusions in relation to the regression weighting method we used, and we offer five points that reflect our observations as well as our shared goals. We hope our comments, like their work in this field, will invigorate the pursuit of new ways of examining, and one day resolving, the persistent concern regarding the AI associated with valid selection tests.