{"title":"Beyond the numbers: a reflexive journey of interrogating racial categorization in QuantCrit","authors":"Lucy Arellano Jr, Carlos A Fitch","doi":"10.1016/j.cobeha.2025.101591","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":56191,"journal":{"name":"Current Opinion in Behavioral Sciences","volume":"66 ","pages":"Article 101591"},"PeriodicalIF":3.5000,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Behavioral Sciences","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S235215462500110X","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.