Suppr超能文献

识别本族和其他种族面孔:对面孔空间中种族表征的影响。

Identification of own-race and other-race faces: implications for the representation of race in face space.

作者信息

Byatt Graham, Rhodes Gillian

机构信息

School of Psychology, University of Western Australia, Nedlands, Western Australia, Australia.

出版信息

Psychon Bull Rev. 2004 Aug;11(4):735-41. doi: 10.3758/bf03196628.

Abstract

Own-race faces are recognized more easily than faces of a different, unfamiliar race. According to the multidimensional space (MDS) framework, the poor discriminability of other-race faces is due to their being more densely clustered in face space than own-race faces. Multidimensional scaling analyses of similarity ratings (Caucasian participants, n = 22) showed that other-race (Chinese) faces are more densely clustered in face space. We applied a formal model to test whether the spatial location of face stimuli could account for identification accuracy of another group of Caucasian participants (n = 30). As expected, own-race (Caucasian) faces were identified more accurately (higher hit rate, lower false alarms, and higher A') than other-race faces, which were more densely clustered than own-race faces. A quantitative model successfully predicted identification performance from the spatial locations of the stimuli. The results are discussed in relation to the standard MDS account of race effects and also an alternative "race-feature" hypothesis.

摘要

识别同种族面孔比识别不同的、不熟悉的种族面孔更容易。根据多维空间(MDS)框架,其他种族面孔的辨别能力较差是因为它们在面孔空间中比同种族面孔聚集得更密集。对相似度评级进行的多维尺度分析(白人参与者,n = 22)表明,其他种族(中国人)的面孔在面孔空间中聚集得更密集。我们应用了一个形式模型来测试面孔刺激的空间位置是否能够解释另一组白人参与者(n = 30)的识别准确率。正如预期的那样,同种族(白人)面孔比其他种族面孔识别得更准确(命中率更高、误报率更低、A'更高),而其他种族面孔比同种族面孔聚集得更密集。一个定量模型成功地从刺激的空间位置预测了识别表现。我们结合种族效应的标准MDS解释以及另一种“种族特征”假设对结果进行了讨论。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验