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基于类别的归纳中典型性的两个方面。

The two faces of typicality in category-based induction.

作者信息

Murphy Gregory L, Ross Brian H

机构信息

Department of Psychology, New York University, 6 Washington Place, New York, NY 10003, USA.

出版信息

Cognition. 2005 Mar;95(2):175-200. doi: 10.1016/j.cognition.2004.01.009.

Abstract

Studies of category-based induction using different methods have found somewhat contradictory results for whether typical items are a stronger basis for induction. Typical category items are generally more similar to other category items than are atypical ones, and they are also more likely to be categorized into the category in question. We propose that the first aspect (representativeness) influences induction, but the second (uncertainty about the correct category) does not. Two experiments using artificial categories found support for this prediction. Two further experiments manipulated pictures of objects and also found that representativeness in the category influenced the strength of induction, but uncertainty of classification did not. Thus, the two aspects of typicality have different effects on category-based induction.

摘要

使用不同方法进行的基于类别的归纳研究,在典型项目是否是更强的归纳基础这一问题上得出了有些矛盾的结果。典型类别项目通常比非典型项目与其他类别项目更相似,并且它们也更有可能被归入所讨论的类别。我们提出,第一个方面(代表性)影响归纳,但第二个方面(关于正确类别的不确定性)则不然。使用人工类别的两项实验为这一预测提供了支持。另外两项实验对物体图片进行了操控,也发现类别中的代表性影响归纳强度,但分类的不确定性则没有。因此,典型性的这两个方面对基于类别的归纳有不同影响。

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