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共变与量词极性:什么决定了短文中的因果归因?

Covariation and quantifier polarity: what determines causal attribution in vignettes?

作者信息

Majid Asifa, Sanford Anthony J, Pickering Martin J

机构信息

Max Planck Institute for Psycholinguistics, AH Nijmegen, The Netherlands.

出版信息

Cognition. 2006 Feb;99(1):35-51. doi: 10.1016/j.cognition.2004.12.004. Epub 2005 Mar 4.

Abstract

Tests of causal attribution often use verbal vignettes, with covariation information provided through statements quantified with natural language expressions. The effect of covariation information has typically been taken to show that set size information affects attribution. However, recent research shows that quantifiers provide information about discourse focus as well as covariation information. In the attribution literature, quantifiers are used to depict covariation, but they confound quantity and focus. In four experiments, we show that focus explains all (Experiment 1) or some (Experiment 2-4) of the impact of covariation information on the attributions made, confirming the importance of the confound. Attribution experiments using vignettes that present covariation information with natural language quantifiers may overestimate the impact of set size information, and ignore the impact of quantifier-induced focus.

摘要

因果归因测试通常使用文字描述的情景,通过用自然语言表达进行量化的陈述来提供共变信息。共变信息的作用通常被认为表明集合大小信息会影响归因。然而,最近的研究表明,量词既提供有关话语焦点的信息,也提供共变信息。在归因文献中,量词用于描述共变,但它们混淆了数量和焦点。在四项实验中,我们表明焦点解释了共变信息对所做归因的全部影响(实验1)或部分影响(实验2 - 4),证实了这种混淆的重要性。使用带有自然语言量词呈现共变信息的情景进行的归因实验可能高估了集合大小信息的影响,而忽略了量词引起的焦点的影响。

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