Reconsidering the “bias” in “the correspondence bias”.

IF 1 Q3 PSYCHOLOGY, MULTIDISCIPLINARY
Drew Walker, Kevin A. Smith, E. Vul
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引用次数: 0

Abstract

We do not directly observe the internal qualities of others so we must infer them from behavior. Although classic attribution theories agree that we consider situational pressures when estimating such internal qualities, one of the best-known results in psychology is that we are prone to a correspondence bias: That we draw inferences from behavior, even when we know that the situation has constrained the action. Dozens of theoretical accounts have sought to explain this result, with the most famous being the proposal that we commit a fundamental attribution error: We are systematically biased to underappreciate the in fl uence of external factors and thus overattribute behavior to disposition. Although there remains disagreement about why we attribute constrained behavior to disposition, most researchers agree that this tendency is in fact an error . We propose that the social judgments made in classic attitude attribution studies have been widely interpreted as reasoning errors only because they have been compared to an inappropriate benchmark, predicated on the assumption of deterministic dispositions and situations. Building from earlier probabilistic accounts, we review classic results that demonstrate that social inferences are consistent with unbiased probabilistic attribution of the in fl uence of situations and dispositions in an uncertain world.
对“对应偏差”中“偏差”的再认识。
我们不能直接观察别人的内在品质,所以我们必须从行为中推断出来。尽管经典的归因理论认为,我们在评估这些内在品质时考虑了情境压力,但心理学中最著名的结果之一是,我们容易产生对应偏差:我们从行为中推断,即使我们知道情境限制了我们的行为。许多理论都试图解释这一结果,其中最著名的是我们犯了基本归因错误的建议:我们系统性地倾向于低估外部因素的影响,从而将行为过度归因于性格。尽管对于为什么我们把受约束的行为归因于性格仍然存在分歧,但大多数研究人员都认为这种倾向实际上是一种错误。我们认为,在经典态度归因研究中做出的社会判断被广泛解释为推理错误,只是因为它们被与一个不恰当的基准进行了比较,该基准是基于确定性倾向和情境的假设。从早期的概率账户中,我们回顾了经典的结果,这些结果表明,在不确定的世界中,社会推断与情况和倾向的影响的无偏概率归因是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Decision-Washington
Decision-Washington PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
2.10
自引率
6.70%
发文量
58
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