Joshua Quint, Chantelle Matagi, Joseph Keawe'aimoku Kaholokula
{"title":"夏威夷国民健康保险协会数据分解法令:通过全州种族和族裔标准防止数据种族灭绝。","authors":"Joshua Quint, Chantelle Matagi, Joseph Keawe'aimoku Kaholokula","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Federal race and ethnicity data standards are commonly applied within the state of Hawai'i. When a multiracial category is used, Native Hawaiians are disproportionately affected since they are more likely than any other group to identify with an additional race or ethnicity group. These data conventions contribute to a phenomenon known as data genocide - the systematic erasure of Indigenous and marginalized peoples from population data. While data aggregation may be unintentional or due to real or perceived barriers, the obstacles to disaggregating data must be overcome to advance health equity. In this call for greater attention to relevant social determinants of health through disaggregation of race and ethnicity data, the history of data standards is reviewed, the implications of aggregation are discussed, and recommended disaggregation strategies are provided.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"67-72"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612414/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Hawai'i NHPI Data Disaggregation Imperative: Preventing Data Genocide Through Statewide Race and Ethnicity Standards.\",\"authors\":\"Joshua Quint, Chantelle Matagi, Joseph Keawe'aimoku Kaholokula\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Federal race and ethnicity data standards are commonly applied within the state of Hawai'i. When a multiracial category is used, Native Hawaiians are disproportionately affected since they are more likely than any other group to identify with an additional race or ethnicity group. These data conventions contribute to a phenomenon known as data genocide - the systematic erasure of Indigenous and marginalized peoples from population data. While data aggregation may be unintentional or due to real or perceived barriers, the obstacles to disaggregating data must be overcome to advance health equity. In this call for greater attention to relevant social determinants of health through disaggregation of race and ethnicity data, the history of data standards is reviewed, the implications of aggregation are discussed, and recommended disaggregation strategies are provided.</p>\",\"PeriodicalId\":36659,\"journal\":{\"name\":\"Hawai''i journal of health & social welfare\",\"volume\":\"82 10 Suppl 1\",\"pages\":\"67-72\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612414/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hawai''i journal of health & social welfare\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hawai''i journal of health & social welfare","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
The Hawai'i NHPI Data Disaggregation Imperative: Preventing Data Genocide Through Statewide Race and Ethnicity Standards.
Federal race and ethnicity data standards are commonly applied within the state of Hawai'i. When a multiracial category is used, Native Hawaiians are disproportionately affected since they are more likely than any other group to identify with an additional race or ethnicity group. These data conventions contribute to a phenomenon known as data genocide - the systematic erasure of Indigenous and marginalized peoples from population data. While data aggregation may be unintentional or due to real or perceived barriers, the obstacles to disaggregating data must be overcome to advance health equity. In this call for greater attention to relevant social determinants of health through disaggregation of race and ethnicity data, the history of data standards is reviewed, the implications of aggregation are discussed, and recommended disaggregation strategies are provided.