Reducing Contextual Bias In Performance Appraisal

摘要 * 0011132Douglas H.韦德尔在我们的社会中广泛使用评估工具。 业绩评估就是这样一种工具，它是重要人事决策的基础，如加薪分配或晋升或解雇建议。 由于业绩评估强烈依赖于主观判断，它很容易受到系统性偏见或扭曲。 在绩效评估中反复出现的一种偏见是背景对比。 这种偏见包括在评估其他工作记录较差的员工后，对一个人的工作表现的评价高于评估那些工作记录较好的员工。这种情境依赖性是评估中一个严重的错误来源，威胁着它的可靠性和有效性。本项目探讨了不同的程序，旨在减少或消除绩效评估中的情境对比，从而创造更可靠和有效的评估技术。材料包括假设员工的绩效档案，包括他们工作记录的几个方面的信息。 在每个实验中，对比偏差是通过让参与者在评估材料核心集之前评估不同的材料集来诱导的。 本研究的目的是开发评估程序，在不同的背景下对核心材料产生相同的判断。这些程序包括操纵类别标签、判断类型和训练方法。实验将测试在多大程度上，包括明确的例子，为不同的类别水平将减少语境偏见。 另外的实验将测试两个选择性判断任务，比较和相似性判断，消除对比效应的有效性。 最后，另一系列实验探索了不同训练方案消除情境偏见的潜力。这项研究的目的是开发可以在商业、教育和政府中实施的程序，以产生更可靠和有效的评估。

Abstract***0011132Douglas H. WedellThere is widespread use of assessment tools in our society. Performanceappraisal is one such tool that serves as a basis for important personneldecisions, such as allocation of raises or recommendation for promotion ortermination. Because performance appraisal strongly relies on subjectivejudgment, it is susceptible to systematic biases or distortions. One suchbias that has been repeatedly demonstrated in performance appraisal iscontextual contrast. This bias consists of the tendency to rate a person'swork performance higher after assessing other employees with poorer workrecords than after assessing those with better work records. Such contextualdependency represents a serious source of error in assessment, threatening itsreliability and validity.This project explores different procedures designed to reduce or eliminatecontextual contrast in performance appraisal and thereby create more reliableand valid assessment techniques. Materials consist of performance profiles ofhypothetical employees that include information on several facets of theirwork records. In each experiment, the contrast bias is induced by havingparticipants evaluate different sets of materials prior to assessing a coreset of materials. The aim of the research is to develop assessment proceduresthat will produce the same judgments of core materials across differentcontexts. These procedures include manipulating category labels, types ofjudgments, and training methods. Experiments will test the degree to whichincluding clear examples for the different category levels will reducecontextual bias. Additional experiments will test the efficacy of twoalternative judgment tasks, comparative and similarity judgment, foreliminating contrast effects. Finally, another series of experiments exploresthe potential for different training regimens to eliminate contextual bias.The aim of this research is to develop procedures that could be implemented inbusiness, education, and government to produce more reliable and validassessments.***