Abstract
Eighty-six incumbents of three different jobs produced job-analytic ratings using either a decomposed (task-based) or a holistic (job-based) rating strategy. Approximately half of them received rater training in making inferential decisions. When tasks were less complex than the job as a whole, rating decomposition generally had positive effects on ratings' quality. Similarly, when the number of tasks rated was low to moderate, rater training was effective. A contingency approach, where limitations concerning the use of rating decomposition and inferential training were outlined, should serve to inform future uses and theories of rating aids in job analysis.
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We would like to acknowledge David Dorsey for his significant contribution to the rater training program. This article is a summary of the doctoral dissertation of Juan Sanchez, which was conducted under the supervision of Edward Levine.
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Sanchez, J.I., Levine, E.L. The impact of raters' cognition on judgment accuracy: An extension to the job analysis domain. J Bus Psychol 9, 47–57 (1994). https://doi.org/10.1007/BF02230986
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DOI: https://doi.org/10.1007/BF02230986