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Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI

机译:非洲裔美国人的微侵略,歧视和表型:肤色和BMI影响的潜在类别分析

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摘要

Data from the 2001-2003 National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N = 3343). Latent class analysis is used to identify four classes of discriminatory treatment: (1) low levels of discrimination, (2) disrespect and condescension, (3) character-based discrimination, and (4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low-level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high-level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.
机译:2001-2003年《美国生活国家调查》的数据用于调查表型对非裔美国人歧视中日常经历的影响(N = 3343)。潜在类别分析用于识别四类歧视待遇:(1)歧视程度低;(2)不尊重和谦逊;(3)基于字符的歧视;(4)歧视程度高。然后,我们使用潜在类多项式逻辑回归来评估肤色和体重与这四类歧视之间的关联。通过将低水平歧视人群指定为参考人群,研究结果表明,皮肤较黑的受访者更有可能被归类为不尊重/自尊心和高级微攻击类型。尽管性别和BMI之间存在显着的相互作用,但BMI与歧视类型无关。体重指数与不尊重和自尊心类型的成员之间有强烈的正相关关系,而男性却没有。这些发现表明肤色和体重是影响非裔美国人遭受歧视的类型和频率的两个表型特征。

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  • 来源
    《Sociological Inquiry》 |2017年第2期|233-255|共23页
  • 作者单位

    Texas A&M Univ, Race & Ethn Studies Inst, 4249 TAMU, College Stn, TX 77843 USA;

    Case Western Reserve Univ, Jack Joseph & Morton Mandel Sch Appl Sci, Cleveland, OH 44106 USA;

    Univ Michigan, Ann Arbor, MI 48109 USA;

    Univ Michigan, Ann Arbor, MI 48109 USA;

    Rutgers State Univ, Aging Res, New Brunswick, NJ USA;

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