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多维尺度分析自身和跨种族面孔空间。

A multidimensional scaling analysis of own- and cross-race face spaces.

机构信息

Department of Psychology, Arizona State University, Tempe, Arizona 85287-1104, United States.

出版信息

Cognition. 2010 Aug;116(2):283-8. doi: 10.1016/j.cognition.2010.05.001. Epub 2010 May 23.

Abstract

We examined predictions derived from Valentine's (1991) Multidimensional Space (MDS) framework for own- and other-race face processing. A set of 20 computerized faces was generated from a single prototype. Each face was saved as Black and White, changing only skin tone, such that structurally identical faces were represented in both race categories. Participants made speeded "same-different" judgments to all possible combinations of faces, from which we generated psychological spaces, with "different" RTs as the measure of similarity. Consistent with the MDS framework, all faces were pseudo-normally distributed around the (unseen) prototype. The distribution of faces was consistent with Valentine's (1991) predictions: despite their physical identity to the White faces, Black faces had lower mean inter-object distances in psychological space. Other-race faces are more densely clustered in psychological space, which could underlie well-known recognition deficits.

摘要

我们检验了 Valentine(1991)多维空间(MDS)框架对自身和他人种族面孔处理的预测。从一个原型生成了一组 20 张计算机化面孔。每张脸都被保存为黑白两种颜色,只改变肤色,使得结构相同的脸在两个种族类别中都有代表。参与者对所有可能的面孔组合进行了快速的“相同-不同”判断,我们从这些判断中生成了心理空间,以“不同”的 RT 作为相似性的衡量标准。与 MDS 框架一致,所有的面孔都围绕着(未看到的)原型呈伪正态分布。面孔的分布与 Valentine(1991)的预测一致:尽管与白人面孔在物理上相同,但黑人面孔在心理空间中的对象间距离平均值较低。异族面孔在心理空间中更密集地聚集,这可能是众所周知的识别缺陷的基础。

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