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迈向一种关于人类面孔跨文化独特性和典型性的新方法:跨群体典型性/独特性度量

Toward a New Approach to Cross-Cultural Distinctiveness and Typicality of Human Faces: The Cross-Group Typicality/ Distinctiveness Metric.

作者信息

Kleisner Karel, Pokorný Šimon, Saribay S Adil

机构信息

Department of Philosophy and History of Science, Charles University, Prague, Czechia.

Department of Psychology, Boǧaziçi University, Istanbul, Turkey.

出版信息

Front Psychol. 2019 Jan 31;10:124. doi: 10.3389/fpsyg.2019.00124. eCollection 2019.

Abstract

In the present research, we took advantage of geometric morphometrics to propose a data-driven method for estimating the individual degree of facial typicality/distinctiveness for cross-cultural (and other cross-group) comparisons. Looking like a stranger in one's home culture may be somewhat stressful. The same facial appearance, however, might become advantageous within an outgroup population. To address this fit between facial appearance and cultural setting, we propose a simple measure of distinctiveness/typicality based on position of an individual along the axis connecting the facial averages of two populations under comparison. The more distant a face is from its ingroup population mean toward the outgroup mean the more distinct it is (vis-à-vis the ingroup) and the more it resembles the outgroup standards. We compared this new measure with an alternative measure based on distance from outgroup mean. The new measure showed stronger association with rated facial distinctiveness than distance from outgroup mean. Subsequently, we manipulated facial stimuli to reflect different levels of ingroup-outgroup distinctiveness and tested them in one of the target cultures. Perceivers were able to successfully distinguish outgroup from ingroup faces in a two-alternative forced-choice task. There was also some evidence that this task was harder when the two faces were closer along the axis connecting the facial averages from the two cultures. Future directions and potential applications of our proposed approach are discussed.

摘要

在本研究中,我们利用几何形态测量学提出了一种数据驱动的方法,用于估计个体面部典型性/独特性的程度,以进行跨文化(及其他跨群体)比较。在自己的文化中看起来像个陌生人可能会有些压力。然而,同样的面部特征在群体外的人群中可能会变得具有优势。为了探讨面部特征与文化背景之间的这种契合关系,我们基于个体在连接两个被比较群体面部平均值的轴线上的位置,提出了一种简单的独特性/典型性度量方法。一张脸离其所属群体的平均值越远,越接近群体外的平均值,它就越独特(相对于所属群体而言),也就越接近群体外的标准。我们将这种新的度量方法与基于离群体外平均值的距离的另一种度量方法进行了比较。新的度量方法与面部独特性评分的关联性比离群体外平均值的距离更强。随后,我们对面部刺激进行了处理,以反映不同程度的群体内-群体外独特性,并在其中一种目标文化中对其进行了测试。在一项二选一的强制选择任务中,感知者能够成功地区分群体外和群体内的面孔。也有一些证据表明,当两张脸在连接两种文化面部平均值的轴线上靠得更近时,这项任务会更难。我们还讨论了所提出方法的未来方向和潜在应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/6365443/148a1f762f9b/fpsyg-10-00124-g001.jpg

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