Beyond Wokeness: Why We Should All Be Using a More "Sensitive" Measure of Self-Reported Gender Identity.

IF 1.7 4区 心理学 Q2 PSYCHOLOGY, MULTIDISCIPLINARY Psychological Reports Pub Date : 2024-10-01 Epub Date: 2023-01-03 DOI:10.1177/00332941221149178
Melissa Marcotte, Marta Cichoń, Nathan DeSalvo, Kayla Medeiros, Stephen Gadbois, Jennifer Alberti-Silverstein
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Abstract

Gender plays a significant role in an individual's experiences and behaviors, as well as their expectations of others. Researchers have long operationalized gender using limited, mutually exclusive categories that fail to capture the rich variability within a gender-diverse population. While open-ended responses or multi-item scales may be a socially progressive approach and necessary for some gender-based research (e.g., Bauer et al., 2017), it may be unsuitable and statistically unfeasible for quantitative researchers in other areas. We analyzed responses from over 700 gender-diverse participants in the U.S. on a series of unipolar scales (i.e., gender identity, expression, and perception by others) that granted participants the flexibility of selecting a comprehensive self-definition while still enabling quantitative analysis of group differences as well as capturing maximum within-group variability. Using a cluster analysis, we found that participants' responses were best represented by five categories: Archetypical Men (n = 169), Archetypical Women (n = 168), Intertypical Men (n = 158), Intertypical Women (n = 126), and Nonconforming (n = 85). We explore the variability of characteristics and beliefs (e.g., gender norms, sexist beliefs) within and between traditional sex and these new gender categories. In this paper, we discuss theoretical considerations for future research and how using this comprehensive operationalization of gender can expand our understanding of "gender differences'' beyond the current scientific assumptions and barriers.

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超越 "职业女性":为什么我们都应该使用更 "敏感 "的自我性别认同测量方法?
性别在个人的经历和行为以及对他人的期望中扮演着重要角色。长期以来,研究人员一直使用有限的、相互排斥的类别来操作性别,但这些类别无法捕捉到性别多元化人群中的丰富变异性。虽然开放式回答或多项目量表可能是一种社会进步的方法,对于某些基于性别的研究也是必要的(例如,Bauer 等人,2017 年),但对于其他领域的定量研究人员来说,这种方法可能并不适合,而且在统计学上也不可行。我们分析了美国 700 多名性别多元化参与者对一系列单极量表(即性别认同、性别表达和他人认知)的回答,这些量表既能让参与者灵活选择全面的自我定义,又能对群体差异进行定量分析,并最大限度地捕捉群体内的变异性。通过聚类分析,我们发现五个类别最能代表参与者的回答:典型男性(n = 169)、典型女性(n = 168)、跨典型男性(n = 158)、跨典型女性(n = 126)和不合群(n = 85)。我们探讨了传统性别和这些新性别类别内部和之间的特征和信念(如性别规范、性别歧视信念)的可变性。在本文中,我们讨论了未来研究的理论考虑因素,以及使用这种全面的性别操作化方法如何能够超越当前的科学假设和障碍,扩大我们对 "性别差异 "的理解。
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来源期刊
Psychological Reports
Psychological Reports PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
5.10
自引率
4.30%
发文量
171
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