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The Automatic Social Categorization Test: Validating a New Measure.

机译:自动社会分类测试:验证一项新措施。

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摘要

Categorization is an essential process in making sense of the world. However, it simplifies perception in a way that distorts reality to some degree. For instance, the color spectrum is a continuum of wavelengths; but colors are grouped into linguistically defined categories (Berlin & Kay, 1969). Although people can tell the difference between different hues within a category, they are better at discriminating colors from different categories than colors from the same category, even if they differ by the same degree in terms of physical wavelength. Hamad (2003) describes this process as 'warping' perceived similarities and differences so as to compress some things into the same category and separate others into different categories." This dissertation describes the Automatic Social Categorization Test (ASCAT), a new way to measure the extent to which this process occurs for social categories (e.g., gender, age, race) by examining confusion errors among stimuli that vary continuously between two categories. We operationally define automatic categorical perception as the degree to which confusion rates are higher for a pair of stimuli within the same subjective category than for a pair belonging to different subjective categories. We first present a series of validation studies with non-social stimuli, showing that automatic categorical perception is stronger for categorical stimuli (i.e., with a gap in the middle) than for continuous stimuli. Next, we extend our method to social stimuli (i.e., morphed faces varying in racial composition), demonstrating a categorical trend that is reduced when social information is removed (i.e., when the faces are scrambled). The degree of automatic social categorization also depends on which social category is presented; faces varying in gender and race are perceived more categorically than faces varying in age. Finally, we show that there are reliable individual differences in automatic race categorization that cannot be attributed to working memory ability or differential fatigue effects. Performance on the ASCAT is also relatively stable across multiple testing sessions. These results suggest that the ASCAT is a useful new tool for research on the correlates and consequences of automatic social categorization.
机译:分类是理解世界的重要过程。但是,它以某种程度上扭曲了现实的方式简化了感知。例如,色谱是波长的连续体。但是颜色被分为语言定义的类别(Berlin&Kay,1969)。尽管人们可以分辨类别中不同色调之间的差异,但是即使它们在物理波长上相差相同程度,他们也比区分相同类别的颜色更好地区分了不同类别的颜色。哈马德(2003)将这一过程描述为“扭曲”感知到的异同,以便将某些事物压缩到相同的类别中,而将其他事物压缩到不同的类别中。”本文描述了自动社会分类测试(ASCAT),这是一种新的衡量方法通过检查两个类别之间连续变化的刺激之间的混淆错误,对社会类别(例如性别,年龄,种族)进行此过程的程度我们在操作上将自动分类感知定义为一对混淆程度较高的程度首先,我们对非社会性刺激进行了一系列验证研究,结果表明,对于分类性刺激,自动分类感知更强(即中间有一个缺口) ),而不是持续刺激。接下来,我们将方法扩展到社会刺激(即,在种族差异方面变脸的人位置),这表明分类趋势在删除社交信息时(即当面孔打乱时)降低了。自动社会分类的程度还取决于所呈现的社会类别。与年龄不同的面孔相比,性别和种族不同的面孔更为明显。最后,我们表明在自动比赛分类中存在可靠的个体差异,不能归因于工作记忆能力或差异性疲劳效应。在多个测试会话中,ASCAT的性能也相对稳定。这些结果表明,ASCAT是研究自动社会分类的相关性和后果的有用的新工具。

著录项

  • 作者

    Sedlins, Mara P.;

  • 作者单位

    University of Washington.;

  • 授予单位 University of Washington.;
  • 学科 Sociology Theory and Methods.;Psychology Cognitive.;Psychology Personality.;Psychology Social.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 91 p.
  • 总页数 91
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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