Automated calibration training for forecasters

IF 1.8 3区 心理学 Q3 PSYCHOLOGY, APPLIED Journal of Behavioral Decision Making Pub Date : 2023-06-28 DOI:10.1002/bdm.2334
Eric R. Stone, Jason Luu, Cory K. Costello, Annie H. Somerville
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Abstract

In two studies, we investigated the effectiveness of an automated form of calibration training via individualized feedback as a means to improve calibration in forecasts. In Experiment 1, this training procedure was tested in a realistic forecasting situation, namely, predicting the outcome of baseball games. Experiment 2 was similar but used a more controlled forecasting task, predicting whether competitors would bust in a modified version of blackjack. In comparison to a control group without training, participants provided with calibration training had reduced confidence levels, which translated into reduced overconfidence and better overall calibration in Experiment 2. The results across both studies suggest that an automated form of individualized performance feedback can reduce the confidence of initially overconfident forecasters.

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预报员的自动校准训练
在两项研究中,我们调查了通过个性化反馈的自动化校准训练形式作为改进预测校准的一种手段的有效性。在实验1中,我们在一个现实的预测情境中,即预测棒球比赛的结果,对这个训练过程进行了测试。实验二类似,但使用了一个更可控的预测任务,预测竞争对手是否会在一个修改版的21点游戏中失败。与未接受培训的对照组相比,接受过校准培训的参与者的置信水平降低了,这转化为实验2中过度自信的减少和更好的整体校准。两项研究的结果都表明,一种自动化的个性化绩效反馈形式可以降低最初过于自信的预测者的信心。
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来源期刊
CiteScore
4.40
自引率
5.00%
发文量
40
期刊介绍: The Journal of Behavioral Decision Making is a multidisciplinary journal with a broad base of content and style. It publishes original empirical reports, critical review papers, theoretical analyses and methodological contributions. The Journal also features book, software and decision aiding technique reviews, abstracts of important articles published elsewhere and teaching suggestions. The objective of the Journal is to present and stimulate behavioral research on decision making and to provide a forum for the evaluation of complementary, contrasting and conflicting perspectives. These perspectives include psychology, management science, sociology, political science and economics. Studies of behavioral decision making in naturalistic and applied settings are encouraged.
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