Document Type
Article
Publication Date
2024
Publication Title
Industrial and Organizational Psychology
Abstract
Foster et al. (2024) offer compelling insights into the advancement of selection measurement assessments, emphasizing high construct validity and accurate predictive capabilities for evaluating candidates’ work performance. Previous arguments surrounding the validity of selection assessments and the predictive performance abilities they encompass have been centered on viewing the measurement system as the culprit of error or have placed a heavy emphasis on understanding the noncognitive influences of raters, such as social contexts (Spence & Keeping, 2011). Foster et al. (2024) provide six recommendations of ways in which the field may benefit from shifting focus away from the measurement tool but rather toward other factors. Instead of elaborating on all recommendations provided in the focal article, this commentary will address and elaborate upon the broadly mentioned first recommendation and propose an additional method for understanding the root causes of rater error and variance in ratings. This commentary concludes with how to make approaches to predicting variance and correcting for error more specific to the cognitive processes of the rater.
Funding Source
This article was published Open Access thanks to a transformative agreement between Milner Library and Cambridge University Press.
Recommended Citation
Anderson P. Decoding variance and predictive ability in selection systems: An application of Gauthier’s framework of rater cognitions. Industrial and Organizational Psychology. 2024;17(3):322-325. doi:10.1017/iop.2024.18
DOI
10.1017/iop.2024.18
Comments
First published in Industrial and Organizational Psychology: https://doi.org/10.1017/iop.2024.18
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.