弱证据效应的语用解释。

Q1 Social Sciences Open Mind Pub Date : 2022-09-28 eCollection Date: 2022-01-01 DOI:10.1162/opmi_a_00061
Samuel A Barnett, Thomas L Griffiths, Robert D Hawkins
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引用次数: 5

摘要

语言不只是用来传递中性的信息;我们经常试图通过支持某一特定观点来说服别人。劝导对信仰更新的经典描述提出了许多挑战,因为信息不能只看表面价值。当演讲者引入新信息时,听众应该如何解释演讲者的“隐藏议程”?在这里,我们扩展了最近的递归社会推理的概率模型,以允许有说服力的目标,并表明我们的模型提供了一个实用的解释,为什么弱有利的论点可能适得其反,这种现象被称为弱证据效应。至关重要的是,该模型预测了信念更新和对信息源的期望之间的系统关系:当演讲者被期望在有说服力的目标下行动并倾向于最有力的证据时,弱证据只会适得其反。我们引入了一个简单的实验范式,称为“木棍竞赛”,以衡量弱证据效应对说话者期望的依赖程度,并表明语用听众模型比其他模型更能解释经验数据。我们的发现为社会推理的理性模型进一步阐明经典决策现象提供了途径。
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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A Pragmatic Account of the Weak Evidence Effect.

Language is not only used to transmit neutral information; we often seek to persuade by arguing in favor of a particular view. Persuasion raises a number of challenges for classical accounts of belief updating, as information cannot be taken at face value. How should listeners account for a speaker's "hidden agenda" when incorporating new information? Here, we extend recent probabilistic models of recursive social reasoning to allow for persuasive goals and show that our model provides a pragmatic account for why weakly favorable arguments may backfire, a phenomenon known as the weak evidence effect. Critically, this model predicts a systematic relationship between belief updates and expectations about the information source: weak evidence should only backfire when speakers are expected to act under persuasive goals and prefer the strongest evidence. We introduce a simple experimental paradigm called the Stick Contest to measure the extent to which the weak evidence effect depends on speaker expectations, and show that a pragmatic listener model accounts for the empirical data better than alternative models. Our findings suggest further avenues for rational models of social reasoning to illuminate classical decision-making phenomena.

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来源期刊
Open Mind
Open Mind Social Sciences-Linguistics and Language
CiteScore
3.20
自引率
0.00%
发文量
15
审稿时长
53 weeks
期刊最新文献
Approximating Human-Level 3D Visual Inferences With Deep Neural Networks. Prosodic Cues Support Inferences About the Question's Pedagogical Intent. The Double Standard of Ownership. Combination and Differentiation Theories of Categorization: A Comparison Using Participants' Categorization Descriptions. Investigating Sensitivity to Shared Information and Personal Experience in Children's Use of Majority Information.
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