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Quantification of evaluations
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AI
DOI：10.1016/j.jesp.2023.104558.png)
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While some evaluation scales ask people to express their judgments of targets using labels on a scale (e.g., very good), some other scales quantify these labels (e.g., 7 = very good). Although the quantified and non -quantified scales may seem identical in terms of the evaluation content, we suggest that quantification in itself significantly influences people's evaluations of targets. We find that evaluators are less likely to use the endpoints-both positive and negative-of quantified evaluation scales, resulting in more conservative evaluations of targets (as compared with non -quantified scales). The effect is more pronounced when targets are of overall positive or negative quality, where endpoints are more relevant. Finally, the effect of quantification is reduced when the endpoints of the scales themselves represent extreme evaluations (e.g., best possible), because people generally refrain from using such extreme endpoints regardless of quantification. We discuss the implications of our findings in terms of other important issues such as rating inflation and quantification of personal activities.
Keyword:
Quantification
Evaluation
Judgment
Rating
Number
期刊
IF:
3.1
论文数:
3.7K
被引数:
1.5W
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