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在无知与真理之间:不确定性判断中的划分依赖与学习

Between ignorance and truth: Partition dependence and learning in judgment under uncertainty.

作者信息

See Kelly E, Fox Craig R, Rottenstreich Yuval S

机构信息

Department of Management and Organizations, Stern School of Business, New York University, New York, NY 10012, USA.

出版信息

J Exp Psychol Learn Mem Cogn. 2006 Nov;32(6):1385-402. doi: 10.1037/0278-7393.32.6.1385.

DOI:10.1037/0278-7393.32.6.1385
PMID:17087591
Abstract

In 3 studies, participants viewed sequences of multiattribute objects (e.g., colored shapes) appearing with varying frequencies and judged the likelihood of the attributes of those objects. Judged probabilities reflected a compromise between (a) the frequency with which each attribute appeared and (b) the ignorance prior probability cued by the number of distinct values that the focal attribute could take on. Thus, judged probabilities were partition dependent, varying with the number of events into which the state space was subjectively divided. This bias was diminished among participants more confident in what they learned, was strong and insensitive to level of confidence when ignorance priors were especially salient, and required ignorance priors to be salient only when probabilities were elicited (not during encoding).

摘要

在3项研究中,参与者观看了以不同频率出现的多属性物体(如彩色形状)序列,并判断这些物体属性出现的可能性。判断概率反映了以下两者之间的折衷:(a)每个属性出现的频率,以及(b)由焦点属性可能具有的不同值的数量所提示的先验无知概率。因此,判断概率依赖于划分方式,会随着状态空间被主观划分成的事件数量而变化。在对所学内容更有信心的参与者中,这种偏差会减小;当无知先验特别显著时,这种偏差很强且对信心水平不敏感,并且只有在引出概率时(而非编码期间)才需要无知先验显著。

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