Optimizing the efficiency: adverse impact trade-off in personnel classification decisions

Different subgroups display different means on specific performance predictors, leading to the quality- diversity dilemma in the personnel selection context. However, since classification situations still arise in practice, the reality of effect sizes will lead to adverse impact in these personnel decision situations as well. The current method to estimate the classification efficiency given a set of predictors, different subgroups and their characteristics, was extended to yield the adverse impact ratio as well. Additionally, this method was implemented in an algorithm that leads to predictor weights that result in optimal trade-offs between efficiency and diversity

Efficiency and adverse impact of general classification decisions

Classification decisions relate to situations in which a battery of predictors is used to assign individuals to a number of different trajectories. De Corte (2000) proposed a method to estimate the classification efficiency in case the assignment of individuals to trajectories is based on least square criterion estimates. The current paper extends this method to the case where the applicants come from several subpopulations and estimates are no longer only regression weighted. The extension is motivated by the fact that using other than regression based criterion estimates for assigning applicants to the different trajectories may result in classification decisions that show substantially less adverse impact as compared to classifications in which regression based criterion estimates govern the allocation process (De Corte, Lievens & Sackett, 2007). An application of the new analytic method indicates that while classifications based on regression weighted criterion estimates lead to optimal classification efficiency, they also yield substantial adverse impact because many of the most valid predictors, and cognitive ability predictors in particular, show large effect sizes in favor of the so-called majority applicants. Alternatively, general (non regression based) classification decisions lead to a wide range of possible trade-offs between efficiency and diversity where concessions in terms of classification efficiency are compensated by more advantageous levels of adverse impact. The proposed method may be used by practitioners to alleviate the quandary between efficiency and adverse impact in a classification context

Designing pareto-optimal systems for complex selection decisions

Whereas simple selection decisions focus on situations where all applicants apply for a single job, a complex selection situation encompasses vacancies for a number of different positions and applicants that apply simultaneously for one or several of these positions. Given selection predictors, several vacancies, an applicant pool and their characteristics, an analytic method is presented that allows the estimation of the expected selection quality as well as the diversity of these complex selection decisions, based on a single predictor composite score. Additionally, the present paper further discusses the integration of the complex selection prediction method within a broader decision making framework with the purpose of designing complex selection decisions that show a Pareto-optimal balance between the often conflicting goals of selection quality and diversity. Next, the method is used to illustrate how it can lead to substantive contributions when considering the quality-diversity dilemma in a complex selection context. Finally, the decision aid is adopted to demonstrate the importance of applying the appropriate selection format (either the simple or the complex selection format) when exploring the front of Pareto-optimal outcomes of planned selections

Assessing emotional and behavioural problems with the child behaviour checklist: exploring the relevance of adjusting the norms for the Flemisch community

The Child Behaviour Checklist (CBCL) is one of the most frequently used dimensional instruments for screening behavioural and emotional problems in children. In this study the psychometric properties of the CBCL 2001-version and the usefulness of existing US norms within a Flemish community sample were explored. Mothers of young children (N = 170) and school-aged children and adolescents (N = 718) completed the CBCL and the Strengths and Difficulties Questionnaire (SDQ). Reliability of both the CBCL/1½-5 and CBCL/6-18 was excellent. There were substantial correlations between the SDQ and CBCL scales, indicating a good concurrent validity. Significant differences were found when comparing the mean CBCL raw scores of the different subsamples (for different ages and gender groups) with the US norms. Generally spoken, the mean CBCL raw scores as well as the clinical and borderline clinical cutpoints for Flemish children were mostly lower, specifically for the Total Problems score and the Externalising scales

Het diversiteit-validiteitsdilemma in complexe selectiebeslissingen

The diversity-validity dilemma arises when valid selection predictors cause adverse impact. In this paper we discuss the diversity-validity dilemma within the complex selection context, which encompasses an applicant pool and several open positions. Some applicants apply for one of the available positions, while others apply for more than one or even all positions. Complex selection decisions select some applicants and assign them to a specific position. We present two methods to estimate the expected selection quality and adverse impact ratio (AIR) of such decisions, in case they are based on a weighted combination of several predictor scores. Additionally, these two methods are implemented in a multi-objective optimization algorithm to develop complex selection decisions that result in a Pareto-optimal trade-off between selection quality and AIR. Pareto-optimal trade-offs are trade-offs between the two outcomes that cannot be bettered simultaneously by any other (complex selection) decision

Computing pareto-optimal predictor composites for complex selection decisions

A complex selection situation encompasses vacancies for several different positions and applicants that apply simultaneously for one or several of these positions. This article presents an analytic method for estimating the expected selection quality, as well as the adverse impact ratio of these complex selections, when the decisions are based on a single predictor composite score. In addition, the method is integrated within a broader decision-making framework for designing complex selection decisions that show a Pareto-optimal balance between the selection quality and diversity goals. Finally, the decision aid is used to demonstrate the importance of applying the appropriate selection format (either the simple or the complex format) when exploring the front of Pareto-optimal outcomes of planned selections

Designing pareto-optimal systems for complex selection decisions

The current practice of personnel selection faces the challenge of reconciling the often competing goals of obtaining a high-quality as well as a diverse workforce. To address this challenge for simple selections, De Corte, Sackett, and Lievens (2011) propose using Pareto-optimal predictor composites. These composites yield trade-offs between selection quality and selection diversity levels that cannot be improved simultaneously by any other composite. The current article describes how these Pareto-optimal composites and trade-offs can be developed in complex selection situations, which are characterized by vacancies for at least two different positions and applicants that apply either for one or several of these open positions simultaneously. An analytic method that estimates the selection quality and adverse impact of these complex selection decisions is presented and implemented in a multi-objective optimization program, so as to obtain Pareto-optimal predictor composites. The resulting decision aid is subsequently used to illustrate how it can lead to substantive contributions when considering the quality-diversity dilemma in a complex selection context

An Update on the Diversity - Validity Dilemma in Personnel Selection: A Review

As globalization increases and labor markets become substantially more diverse, increasing diversity during personnel selection has become a dominant theme in personnel selection in human resource management. However, while trying to pursue this goal, researchers and practitioners find themselves confronted with the diversity-validity dilemma, as some of the most valid selection instruments display considerable ethnic subgroup differences in test performance. The goal of the current paper is twofold. First, we update and review the literature on the diversity-validity dilemma and discuss several strategies that aim to increase diversity without jeopardizing criterion-related validity. Second, we provide researchers and practitioners with evidence-based guidelines for dealing with the dilemma. Additionally, we identify several new avenues for future research

An Update on the Diversity - Validity Dilemma in Personnel Selection: A Review

As globalization increases and labor markets become substantially more diverse, increasing diversity during personnel selection has become a dominant theme in personnel selection in human resource management. However, while trying to pursue this goal, researchers and practitioners find themselves confronted with the diversity-validity dilemma, as some of the most valid selection instruments display considerable ethnic subgroup differences in test performance. The goal of the current paper is twofold. First, we update and review the literature on the diversity-validity dilemma and discuss several strategies that aim to increase diversity without jeopardizing criterion-related validity. Second, we provide researchers and practitioners with evidence-based guidelines for dealing with the dilemma. Additionally, we identify several new avenues for future research