享有特权但不掌权:亚裔美国科技工作者如何使用种族策略来转移和对抗种族和种族主义。

IF 2.1 3区 社会学 Q2 SOCIOLOGY
Tiffany Y Chow
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引用次数: 1

摘要

对科技工作者的研究往往集中在行业内的种族不平等问题上,但却没有认真地把亚裔美国专业人士视为种族化的对象。本文以亚裔美国人为中心,以其种族身份影响其在高科技行业的职业轨迹和专业经验为中心,解决了这一知识差距。根据对57位亚裔美国技术专业人士的采访,我发现亚裔美国人在工作场所使用四种主要的种族策略来转移或对抗种族主义,其中三种种族策略是种族操纵,本质化,距离,故意将亚裔美国人从种族主义的聚光灯下移开。第四种种族策略,反对,承认种族主义;采用这种种族策略的员工往往对高科技行业的白人权力结构感到非常沮丧,以至于他们别无选择,只能离开主流组织。当地的种族政治和亚洲移民工人的历史影响强化了其中的一些种族策略,他们帮助塑造了旧金山湾区的硅谷和亚裔美国人文化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Privileged but not in Power: How Asian American Tech Workers use Racial Strategies to Deflect and Confront Race and Racism.

Research on tech workers has often focused on racial inequalities within the industry but has failed to seriously consider Asian American professionals as racialized subjects. This paper addresses this knowledge gap by centering Asian Americans as workers whose racial identity impacts their career trajectory and professional experiences in the high-tech industry. Based on 57 interviews with Asian American tech professionals, I find that Asian Americans use four main racial strategies to deflect or confront racism in the workplace Three of these racial strategies-racial maneuvering, essentializing, distancing- intentionally remove Asian Americans from the glare of racism. The fourth racial strategy, dissenting, acknowledges racism; workers using this racial strategy are often so frustrated by the white power structure of the high-tech industry that they find no other choice but to leave mainstream organizations. Several of these racial strategies are reinforced by local racial politics and the historical influence of Asian immigrant workers that helped shape both Silicon Valley and Asian American culture in the San Francisco Bay Area.

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来源期刊
CiteScore
3.60
自引率
0.00%
发文量
17
期刊介绍: Qualitative Sociology is dedicated to the qualitative interpretation and analysis of social life. The journal does not restrict theoretical or analytical orientation and welcomes manuscripts based on research methods such as interviewing, participant observation, ethnography, historical analysis, content analysis and others which do not rely primarily on numerical data.
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