Measuring race and ethnicity for administrative data sets and then analyzing these data to understand racial/ethnic disparities present many logistical and theoretical challenges. In this chapter, we conduct a synthetic review of studies on how to effectively measure race/ethnicity for administrative data purposes and then utilize these measures in analyses. Recommendations based on this synthesis include combining the measure of Hispanic ethnicity with the broader racial/ethnic measure and allowing individuals to select more than one race/ethnicity. Data collection should rely on self-reports but could be supplemented using birth certificates or equivalent sources. Collecting data over time, especially for young people, will help identify multiracial and American Indian populations. For those with more complex racial/ethnic identities, including measures of country of origin, language, and recency of immigration can be helpful in addition to asking individuals which racial/ethnic identity they most identify with. Administrative data collection could also begin to incorporate phenotype measures to facilitate the calculation of disparities within race/ethnicity by skin tone. Those analyzing racial/ethnic disparities should understand how these measures are created and attempt to develop fieldwide terminology to describe racial/ethnic identities.

中文翻译：

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行政数据收集和分析如何更好地反映种族和民族身份

测量行政数据集的种族和民族，然后分析这些数据以了解种族/民族差异，存在许多逻辑和理论挑战。在本章中，我们对如何为行政数据目的有效衡量种族/民族的研究进行综合回顾，然后在分析中利用这些衡量指标。基于此综合的建议包括将西班牙裔种族的衡量标准与更广泛的种族/民族衡量标准相结合，并允许个人选择一个以上的种族/民族。数据收集应依赖于自我报告，但可以使用出生证明或同等来源进行补充。随着时间的推移收集数据，尤其是针对年轻人的数据，将有助于识别多种族和美洲印第安人人口。对于那些具有更复杂种族/民族身份的人，除了询问个人最认同哪种种族/民族身份外，包括原籍国、语言和移民新近程度的措施也很有帮助。行政数据收集也可以开始纳入表型措施，以促进按肤色计算种族/民族内部的差异。分析种族/族裔差异的人应该了解这些措施是如何创建的，并尝试开发用于描述种族/族裔身份的领域术语。