![thisisengineering-raeng-ftd-qk0om20-unsplash_01.jpg](/sites/g/files/omnuum10826/files/styles/hwp_21_9__1920x825/public/datasmart/files/thisisengineering-raeng-ftd-qk0om20-unsplash_01.jpg?itok=vdHaTV1O) # Racial Categories and Public Health Data **How Flattening "American Indian" Harms Communities** November 03, 2022 [ Betsy Gardner ](/betsy-gardner) - November 3, 2022 - [Public Health](/public-health) ## **Lessons for City CDOs** - Gartner recommends that Chief Data Officers understand the Indigenous history of their cities and “understand why there are Native people in cities, because it’s not accidental.” Additionally, CDOs should be familiar with the IHS clinics, community spaces, and other Native resources available in cities as they can be partners in data collection efforts. - McCoy hopes that cities can learn from each other, as there are different kinds of identifications and communities in different urban areas. For example, contemporary community organizing in Chicago is very intertribal as a result of removals and relocation, as compared to Seattle where many members of the urban community are Coast Salish people whose nations have called Seattle home since time immemorial, in addition to many relocated citizens and descendants of other nations. If CDOs know “who was there, who is still there, and who is there now” they will have a better grasp of demographic breakdowns. - “Standards and expectations are shifting,” said Wilbur, and cities have the opportunity to be at the front of that work. By reaching out to various tribes and communities, CDOs will gain better information which in turn creates better policies for their residents. > "We count people, but why do we count them? Who uses this information and for what purposes?" - Danielle Gartner Since the outbreak of the COVID-19 pandemic in late 2019, outbreak data, infection tracking, and hospital capacity dashboards have brought the details of public health data directly to the public in a way previously impossible. One aspect of many dashboards and reports was race; breaking down infections, hospitalizations, vaccinations, and comorbidities by race/ethnicity revealed important discrepancies in care and resources. And it continues to be an important way of breaking down economic recovery, stimulus and benefit needs, access to healthcare, and quality of neighborhood infrastructure. However, the recent paper [“American Indian” as a Racial Category in Public Health: Implications for Communities and Practice](https://ajph-aphapublications-org.ezp-prod1.hul.harvard.edu/doi/pdf/10.2105/AJPH.2021.306465) highlights the challenges in racial categorization and offers recommendations for researchers, public health officials, city leaders, and community members looking to improve data collection. Written by Danielle Gartner, PhD, Rachel Wilbur, MPH, and Meredith McCoy, PhD, MEd, the article not only points to the history of colonialism, but also to current attitudes around [othering Indigenous Americans](https://www.latimes.com/entertainment-arts/tv/story/2020-11-05/it-looks-like-cnn-called-native-americans-something-else-theyre-not-happy) as negatively impacting data collection and public policies. The three co-authors met at the University of North Carolina (UNC) when they were members of the First Nations Graduate Circle. Wilbur, of Tolowa and Chetco descent and currently a postdoctoral fellow in Indigenous wellness at the [Harvard Medical School](https://ghsm.hms.harvard.edu/), said that they connected over their common academic topics and how those intersected with their identities as Indigenous women in academia. Gartner, a citizen of the Sault Saint Marie Tribe of Chippewa Indians and currently an Assistant Professor of Epidemiology and Biostatistics at Michigan State University, also came to this work with a biomedical and public health lens. McCoy, of Turtle Mountain Ojibwe descent, brought a historical perspective to the collaboration and is currently an Assistant Professor in American Studies and History at Carleton College. All three knew that there was already a core group of Indigenous scholars producing strong work in the data sovereignty space and were frustrated that this research remained siloed. This motivated them to write [“American Indian” as a Racial Category in Public Health](https://ajph-aphapublications-org.ezp-prod1.hul.harvard.edu/doi/pdf/10.2105/AJPH.2021.306465) and demonstrate how data sovereignty applied to their respective fields. “We wanted to amplify that work,” said McCoy, “because you can see how scholars have been saying this for a while without a lot of traction.” This article supports their mission and aims to bring relevant insights to city and urban leaders currently engaging with and collecting race/ethnicity data. First, it is important to state why the broad “American Indian” racial categorization is harmful. For Gartner, it’s the fact that “at the end of the day people are using these data to make important policy decisions and the researchers or practitioners are often making racial identification decisions for people.” There are [real world negative impacts for incorrectly categorizing people](https://datasmart.ash.harvard.edu/news/article/they-disappear-not-once-three-times-life-media-and-data), particularly when the categorization of Indigenous populations is rooted in [colonialism](https://conservancy.umn.edu/handle/11299/199061), [racist stereotypes](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3941118/), and [forced assimilation](https://www.npr.org/2008/05/12/16516865/american-indian-boarding-schools-haunt-many). While many current researchers disavow these harmful ideas, it’s important to update the practices to reflect the knowledge, preferences, and identities coming from the populations themselves. Additionally, McCoy described the process of miscategorization as a “cycle of denying Indigenous existence, which leads to denying resources, which then can lead to poor health outcomes.” Unfortunately, it’s impossible to detangle this cycle with the actual [stated intentions](https://www.ou.edu/gaylord/exiled-to-indian-country/content/remembering-the-stories-of-indian-boarding-schools) of [early American leaders](https://www.jstor.org/stable/541345) whose [goal was the elimination](https://history.state.gov/milestones/1830-1860/indian-treaties) and [eradication of Native Americans](https://www.nps.gov/articles/the-expeditions-impact.htm). So while the intentions may be different today, research methods that perpetuated this cycle have caused harm for generations and using them creates bad public policy. Which is why McCoy, Gartner, and Wilbur wrote their set of data collection recommendations, outlined below. ### 1. Look beyond the “deficit focus.” The authors all agreed that research and data collection with Indigenous populations focuses almost exclusively on deficits. In particular they found this in public health fields, where data is collected about negatives in the population (for example prevalence of disease or lack of sanitation). And while it’s important to identify challenge areas, this research ignores the strengths associated with tribal identity. There is ample opportunity to research how being a part of a tribal community improves health, like how certain cultural values contribute to positive mental health and how access to ceremony and traditional medicinal practices provides tangible benefits. ### 2. Consider data disaggregation rather than flattening populations together. Gartner pointed out that many common data practices around race are “things we’re taught to do and we don’t really question, but it’s useless to group people together in this way.” While many practitioners are encouraged to either group small populations as “other” or remove them entirely for being statistically insignificant, the authors identified two harms from this practice. First, future researchers won’t be able to investigate or examine resulting estimates, no matter how imprecise, if they’re removed. “A lot of analysis is conducted on secondary data, so if Native identities are thrown out then we can’t drill down by nation or tribe later,” said Wilbur “We can’t fix that about the past, but why aren’t we doing better now?” And second, the trust between communities and researchers is eroded when people provide their racial/ethnic identity and then suddenly that information is deemed unimportant and disappears in the final product. ### 3. Different research questions require different breakdowns. “It is exceedingly difficult to ask people how to put themselves into categories,” said McCoy, “No population is static so, when talking about Native people, many people have combinations of urban and rural experiences or have connections to multiple tribes.” These permutations mean that there is no one grand recommendation for how to create precise groupings, and instead depends on the individual research question. For example, Wilbur pointed out that a study looking at the impacts of interactions with the federal government would likely categorize by federally recognized tribes, whereas a question about health could compare one community of a tribal nation with the other peer communities in the same nation. ### 4. Understand the cultural context of self-identification. Anyone looking to conduct data collection with Indigenous populations must take the cultural and historic context of identity, sovereignty, and colonialism into account. McCoy acknowledged that the idea of self-identification is complicated, because it requires “affirming the dignity of people who have been disenrolled or are kept out by blood quantum, but also respecting tribal sovereignty and Native nations’ rights to say who is and isn’t Native.” Not only should researchers understand the history of the different communities and ways that individuals can be enrolled or identified as part of different tribes, but they should also heed the above point and preserve granular data on identification for future researchers. ### 5. Respect and engage Indigenous communities during research. Gartner, Wilbur, and McCoy all agreed that research “has to be developed with the community.” Indigenous people deserve to be engaged in the full process, from forming research questions to advising on data collection methods to distributing and sharing results. All three have, unfortunately, seen researchers shy away from this work due to uncertainty, or ignorance, or avoidance. Yet bringing the community into the data collection, research, publication, and implementation not only creates a better product but also fosters trust and more effectively influences policy interventions. In order to pass the mic appropriately, the following researchers are highlighted as influences on the work and leaders in the fields of data sovereignty. Please check out their work to learn more: [Stephanie Fryberg](https://sites.lsa.umich.edu/culturecollab/people/dr-stephanie-fryberg/), University of Michigan; [Krystal Tsosie](https://search.asu.edu/profile/535281), Arizona State University; [Karina Walters](https://socialwork.uw.edu/faculty/professors/karina-l-walters), University of Washington; [Melissa Walls](https://publichealth.jhu.edu/faculty/3363/melissa-l-walls), Johns Hopkins University; [Abigail Echo-Hawk](https://www.uihi.org/people/abigail-echo-hawk-ma/), Urban Indian Health Institute; and [Desi Rodriguez-Lonebear](https://igp.arizona.edu/person/desi-small-rodriguez), University of Arizona. ***\*In this article, the terms Native, Native American, and American Indian/Alaska Native are used interchangeably, in accordance with the Urban Indian Health Institute’s practices. These terms acknowledge the varying ways that North American Indigenous peoples are forced to identify within the American racial structure and English language.*** ## About the Author ### Betsy Gardner ![Headshot of Betsy Gardner](/sites/g/files/omnuum10826/files/styles/hwp_1_1__100x100_scale/public/2025-05/Betsy%20Headshot%20resize.jpg?itok=k2OsSp1g) Betsy Gardner is the editor of Data-Smart City Solutions and the producer of the Data-Smart City Pod. Prior to this, Betsy worked in a variety of roles in higher education, focusing on deconstructing racial and gender inequality through research, writing, and facilitation. She also researched government spending and transparency at the Lincoln Institute of Land Policy. Betsy holds a master’s degree in Urban and Regional Policy from Northeastern University, a bachelor’s degree in Art History from Boston University, and a graduate certificate in Digital Storytelling from the Harvard Extension School. 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