超越数字:在QuantCrit中质疑种族分类的反身之旅

IF 3.5 2区 心理学 Q1 BEHAVIORAL SCIENCES
Lucy Arellano Jr, Carlos A Fitch
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引用次数: 0

摘要

定量方法历来忽视了种族的复杂性,但批判性定量方法和QuantCrit已经出现,挑战了传统方法。本文探讨了一名教师和一名博士生进入QuantCrit的历程,强调了第三条原则:“类别既不是自然的,也不是给定的。”作者对自己的工作进行了批评,与现有文献进行了接触,并提出了未来的方向,包括人工智能在人口分类中的作用和交叉定量分析的潜力。通过质疑严格的分类和倡导方法正义,本文推进了定量研究中种族平等的对话。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond the numbers: a reflexive journey of interrogating racial categorization in QuantCrit
Quantitative methodologies have historically overlooked the complexities of race, yet critical quantitative methods and QuantCrit have emerged to challenge traditional approaches. This paper explores a faculty member’s and a doctoral student’s journeys into QuantCrit, emphasizing the third tenet: “Categories are neither natural nor given.” The authors critique their own work, engage with existing literature, and propose future directions, including artificial intelligence’s role in demographic classification and the potential for intersectional quantitative analyses. By interrogating rigid categorization and advocating for methodological justice, this paper advances the conversation on racial equity in quantitative research.
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来源期刊
Current Opinion in Behavioral Sciences
Current Opinion in Behavioral Sciences Neuroscience-Cognitive Neuroscience
CiteScore
10.90
自引率
2.00%
发文量
135
期刊介绍: Current Opinion in Behavioral Sciences is a systematic, integrative review journal that provides a unique and educational platform for updates on the expanding volume of information published in the field of behavioral sciences.
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