{"title":"种族分析技术:基于种族的平均值会在对种族主义的认知上造成虚幻的群体差异。","authors":"Joel E Martinez","doi":"10.1037/xge0001673","DOIUrl":null,"url":null,"abstract":"Research practices used by social scientists to understand and dismantle the psychological foundations that uphold racist hierarchies can backfire when they rely on racecraft. Racecraft ideology assumes the reality of race(s), an assumption that shapes study designs and inferences to the detriment of theoretical and practical goals. I showcase how racecraft manifests in studies seeking to quantify how perceptions of sociopolitical stimuli differ across racialized perceivers (e.g., black, white, latinx). The typical analysis for quantifying perceptions focuses on comparing group averages, which assumes the existence of discrete \"races\" whose perceptions can be sufficiently summarized by averages. Across three studies, I used variance component analyses on racism ratings of anti-immigrant tweets from differently racialized perceivers (N = 1,211) to show there was much larger disagreement than agreement within race categories, even when there were average differences in perceptions across race categories. This analysis shows how analytic practices can bolster different assumptions about the nature of race, some of which reify the illusion that race categories are stable cohesive groups. Researchers can improve their analytic inferences and avoid producing race-reifying caricatures of peoples' perceptions by adding variance mapping to their toolkits and attending to racialization as a dynamic process-needed improvements within the psychological study of race and racism, group-based beliefs, and antiracist research endeavors. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytic racecraft: Race-based averages create illusory group differences in perceptions of racism.\",\"authors\":\"Joel E Martinez\",\"doi\":\"10.1037/xge0001673\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Research practices used by social scientists to understand and dismantle the psychological foundations that uphold racist hierarchies can backfire when they rely on racecraft. Racecraft ideology assumes the reality of race(s), an assumption that shapes study designs and inferences to the detriment of theoretical and practical goals. I showcase how racecraft manifests in studies seeking to quantify how perceptions of sociopolitical stimuli differ across racialized perceivers (e.g., black, white, latinx). The typical analysis for quantifying perceptions focuses on comparing group averages, which assumes the existence of discrete \\\"races\\\" whose perceptions can be sufficiently summarized by averages. Across three studies, I used variance component analyses on racism ratings of anti-immigrant tweets from differently racialized perceivers (N = 1,211) to show there was much larger disagreement than agreement within race categories, even when there were average differences in perceptions across race categories. This analysis shows how analytic practices can bolster different assumptions about the nature of race, some of which reify the illusion that race categories are stable cohesive groups. Researchers can improve their analytic inferences and avoid producing race-reifying caricatures of peoples' perceptions by adding variance mapping to their toolkits and attending to racialization as a dynamic process-needed improvements within the psychological study of race and racism, group-based beliefs, and antiracist research endeavors. (PsycInfo Database Record (c) 2024 APA, all rights reserved).\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1037/xge0001673\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/xge0001673","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
摘要
社会科学家为了解和瓦解维护种族主义等级制度的心理基础而采取的研究做法,如果依赖于种族思想,就会适得其反。种族意识形态假定了种族的真实性,这种假定影响了研究设计和推论,从而损害了理论和实践目标。我将展示种族法如何体现在寻求量化不同种族感知者(如黑人、白人、拉丁裔)对社会政治刺激的感知差异的研究中。量化感知的典型分析侧重于比较群体平均值,这就假定存在离散的 "种族",其感知可以用平均值充分概括。在三项研究中,我对来自不同种族的感知者(N = 1,211)的反移民推文的种族主义评分进行了方差分析,结果显示,即使不同种族类别的感知存在平均差异,种族类别内的分歧也远远大于一致。这项分析表明了分析实践如何支持对种族本质的不同假设,其中一些假设还强化了种族类别是稳定的内聚群体的假象。研究人员可以改进他们的分析推论,通过在工具包中添加方差图,并将种族化作为一个动态过程来关注,避免产生种族化的人们认知漫画--这是对种族和种族主义的心理学研究、基于群体的信念以及反种族主义研究工作所需要的改进。(PsycInfo Database Record (c) 2024 APA,保留所有权利)。
Analytic racecraft: Race-based averages create illusory group differences in perceptions of racism.
Research practices used by social scientists to understand and dismantle the psychological foundations that uphold racist hierarchies can backfire when they rely on racecraft. Racecraft ideology assumes the reality of race(s), an assumption that shapes study designs and inferences to the detriment of theoretical and practical goals. I showcase how racecraft manifests in studies seeking to quantify how perceptions of sociopolitical stimuli differ across racialized perceivers (e.g., black, white, latinx). The typical analysis for quantifying perceptions focuses on comparing group averages, which assumes the existence of discrete "races" whose perceptions can be sufficiently summarized by averages. Across three studies, I used variance component analyses on racism ratings of anti-immigrant tweets from differently racialized perceivers (N = 1,211) to show there was much larger disagreement than agreement within race categories, even when there were average differences in perceptions across race categories. This analysis shows how analytic practices can bolster different assumptions about the nature of race, some of which reify the illusion that race categories are stable cohesive groups. Researchers can improve their analytic inferences and avoid producing race-reifying caricatures of peoples' perceptions by adding variance mapping to their toolkits and attending to racialization as a dynamic process-needed improvements within the psychological study of race and racism, group-based beliefs, and antiracist research endeavors. (PsycInfo Database Record (c) 2024 APA, all rights reserved).