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基于相似性的自然范畴分类与模糊性

Similarity-based categorization and fuzziness of natural categories.

作者信息

Hampton J A

机构信息

Department of Psychology, City University, London, UK.

出版信息

Cognition. 1998 Jan;65(2-3):137-65. doi: 10.1016/s0010-0277(97)00042-5.

DOI:10.1016/s0010-0277(97)00042-5
PMID:9557381
Abstract

The adequacy of similarity to prototype as an account of categorization in natural concepts was assessed by analyzing the monotonicity of the relation between typicality of an item in a category and the probability of a positive categorization response using data from McCloskey and Glucksberg (1978). The analysis revealed a strong underlying similarity-based threshold curve, with systematic deviations. Further data collection showed that deviations from the curve could be attributed to the effects of unfamiliarity and non-categorical associations on typicality judgments, as well as differences between the perceptual appearance of an item (which tended to boost typicality) and its underlying nature (which tended to boost categorization). The results are discussed in terms of the different presuppositions and task constraints involved in rating typicality as opposed to performing a categorization.

摘要

通过分析使用麦克洛斯基和格鲁克斯伯格(1978年)的数据得出的某一类别中某一项目的典型性与肯定分类反应概率之间关系的单调性,来评估与原型的相似性作为自然概念分类解释的充分性。分析揭示了一条基于相似性的强大潜在阈值曲线,存在系统性偏差。进一步的数据收集表明,与曲线的偏差可归因于不熟悉和非分类关联对典型性判断的影响,以及项目的感知外观(往往会提高典型性)与其内在本质(往往会提高分类)之间的差异。根据对典型性评分与进行分类所涉及的不同预设和任务约束来讨论结果。

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