Operationalizing racialized exposures in historical research on anti-Asian racism and health: a comparison of two methods.
Operationalizing racialized exposures in historical research on anti-Asian racism and health: a comparison of two methods.
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DOI：
10.3389/fpubh.2023.983434
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发表时间：
2023
影响因子：
5.2
通讯作者：
Stern, Alexandra Minna
中科院分区：
文献类型：
--
作者：
Kaniecki, Marie;Novak, Nicole Louise;Gao, Sarah;Harlow, Sioban;Stern, Alexandra Minna
关键词：
解决当代反亚裔种族主义及其对健康的影响，需要了解其历史根源，包括对移民，公民身份和土地所有权的歧视性限制。档案二级数据，如历史人口普查记录，提供了机会，定量分析结构动态，影响亚洲移民和亚裔美国人的健康。普查数据克服了其他数据来源的弱点，如样本规模小和亚洲亚群体的汇总。本文探讨了20世纪初人口普查数据的优势和局限性，以了解亚裔美国人和结构性种族主义。我们使用加州1920-1940年三次十年一次的人口普查数据，比较了识别亚裔美国人的两个标准：人口普查种族类别和亚洲姓氏列表（中国人、印度人、日本人、韩国人和菲律宾人），这些数据在当代人口数据中得到了验证。本文探讨了敏感性和特异性的姓氏分类相比，人口普查指定的“颜色或种族”在人口水平。姓氏标准被认为是高度具体的，与五个姓氏名单中的每一个有超过99%的特异性，所有三个普查年。中国姓氏列表的敏感度最高（在人口普查年份的敏感度范围为0.60-0.67），其次是印度（0.54-0.61）和日本（0.51-0.62）姓氏列表。韩国（0.40-0.45）和菲律宾（0.10-0.21）姓氏的敏感性要低得多。除印第安人姓氏外，1920-1940年人口普查数据中姓氏标准的敏感度值低于1990年人口普查报告的敏感度值。各次群体在普查年份的敏感性和趋势方面的差异程度各不相同。与当代数据相比，姓氏标准在检测历史数据中的亚洲亚组方面的敏感性可能较低，因为亚洲人的计数程序随时间而变化。我们研究了人口普查中种族，民族和国籍的合并如何导致姓氏分类的敏感性低于人口普查指定的“肤色或种族”。这些结果可以指导决策时，具体的研究问题的背景下操作的种族，从而促进历史的定量研究亚裔美国人的经验。此外，这些结果强调，需要在其特定的历史背景下重新考虑种族和种族主义的措施。
Addressing contemporary anti-Asian racism and its impacts on health requires understanding its historical roots, including discriminatory restrictions on immigration, citizenship, and land ownership. Archival secondary data such as historical census records provide opportunities to quantitatively analyze structural dynamics that affect the health of Asian immigrants and Asian Americans. Census data overcome weaknesses of other data sources, such as small sample size and aggregation of Asian subgroups. This article explores the strengths and limitations of early twentieth-century census data for understanding Asian Americans and structural racism. We used California census data from three decennial census spanning 1920–1940 to compare two criteria for identifying Asian Americans: census racial categories and Asian surname lists (Chinese, Indian, Japanese, Korean, and Filipino) that have been validated in contemporary population data. This paper examines the sensitivity and specificity of surname classification compared to census-designated “color or race” at the population level. Surname criteria were found to be highly specific, with each of the five surname lists having a specificity of over 99% for all three census years. The Chinese surname list had the highest sensitivity (ranging from 0.60–0.67 across census years), followed by the Indian (0.54–0.61) and Japanese (0.51–0.62) surname lists. Sensitivity was much lower for Korean (0.40–0.45) and Filipino (0.10–0.21) surnames. With the exception of Indian surnames, the sensitivity values of surname criteria were lower for the 1920–1940 census data than those reported for the 1990 census. The extent of the difference in sensitivity and trends across census years vary by subgroup. Surname criteria may have lower sensitivity in detecting Asian subgroups in historical data as opposed to contemporary data as enumeration procedures for Asians have changed across time. We examine how the conflation of race, ethnicity, and nationality in the census could contribute to low sensitivity of surname classification compared to census-designated “color or race.” These results can guide decisions when operationalizing race in the context of specific research questions, thus promoting historical quantitative study of Asian American experiences. Furthermore, these results stress the need to situate measures of race and racism in their specific historical context.
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影响因子：
12.7
作者：
Fuller-Thomson, Esme;Brennenstuhl, Sarah;Hurd, Marion
通讯作者：
Hurd, Marion
影响因子：
4.5
作者：
Gordon, Nancy P.;Lin, Teresa Y.;Lo, Joan C.
通讯作者：
Lo, Joan C.
DOI：
10.1016/j.ssmph.2016.06.007
发表时间：
2016-12
期刊：
SSM - population health
影响因子：
--
作者：
Cobb RJ;Thomas CS;Laster Pirtle WN;Darity WA Jr
通讯作者：
Darity WA Jr
影响因子：
3.5
作者：
Feigenbaum, James J.;Muller, Christopher;Wrigley-Field, Elizabeth
通讯作者：
Wrigley-Field, Elizabeth
影响因子：
3.1
作者：
El-Sayed AM;Lauderdale DS;Galea S
通讯作者：
Galea S