University of Michigan, Ann Arbor, MI, United States.
University of California, Los Angeles, Los Angeles, CA, United States.
Front Public Health. 2023 Jul 6;11:983434. doi: 10.3389/fpubh.2023.983434. eCollection 2023.
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.
要解决当代反亚裔种族主义及其对健康的影响，就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。档案二次数据（如历史人口普查记录）为定量分析影响亚洲移民和亚裔美国人健康的结构动态提供了机会。人口普查数据克服了其他数据源的弱点，例如样本量小和亚洲子群体的聚合。本文探讨了 20 世纪早期人口普查数据在理解亚裔美国人及结构性种族主义方面的优势和局限性。
我们使用加利福尼亚州三次十年一次的人口普查数据（跨越 1920-1940 年），将两种识别亚裔美国人的标准进行了比较：人口普查种族类别和经当代人口数据验证的亚裔姓氏列表（中国人、印度人、日本人、韩国人和菲律宾人）。本文在人口层面上，比较了姓氏分类与人口普查指定的“肤色或种族”的敏感性和特异性。
姓氏标准被发现具有很高的特异性，在所有三个普查年份中，五个姓氏列表的特异性均超过 99%。中国人的姓氏列表具有最高的敏感性（在普查年份中，范围从 0.60 到 0.67），其次是印度人（0.54 到 0.61）和日本人（0.51 到 0.62）姓氏列表。韩国人（0.40 到 0.45）和菲律宾人（0.10 到 0.21）姓氏的敏感性要低得多。除了印度姓氏外，姓氏标准的敏感性值在 1920-1940 年人口普查数据中低于 1990 年人口普查报告的值。跨普查年份的敏感性和趋势差异因亚群而异。
姓氏标准在检测历史数据中的亚裔亚群时可能不如检测当代数据敏感，因为亚洲人的计数程序随时间发生了变化。我们研究了在人口普查中种族、族裔和国籍的混淆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”。这些结果可以在特定研究问题的背景下指导种族的操作化决策，从而促进亚裔美国人经验的历史定量研究。此外，这些结果强调了将种族和种族主义措施置于其具体历史背景中的必要性。
