Gartner Danielle R, Martinez Rae Anne M
Department of Epidemiology & Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA.
Minnesota Population Center, University of Minnesota, Minneapolis, MN, USA.
Am J Epidemiol. 2025 May 2. doi: 10.1093/aje/kwaf097.
One need not look far for an example of epidemiologic research where Indigenous people have either been excluded from analyses or have been aggregated with other racial and ethnic identities as an "Other." Exclusion and aggregation of Indigenous peoples prevents us from adequately characterizing their health in ways that are useful for collective action. In this commentary we describe three distinct, yet related, issues underlying the relationships between statistical power ($\beta \Big)$ and structural and ideational power related to the "small sample size" problem for Indigenous peoples: (i) inadequate data procurement and management processes, (ii) normative methodological practices, and (iii) insufficient scientific communication. In the spirit of disciplinary reflection and self-critique, we identify and review the manifestation of these issues in one author's previously published research. We then discuss and reemphasize important contributing historical and contemporary systems of injustice, and, finally, summarize existing promising research and analytic practices. Given that the tools that address the health of numerically large groups dominate teaching and research spaces, we must move towards a paradigm shift to fully provide equity, justice, and beneficence to Indigenous peoples and other "numerically small" groups.
在流行病学研究中，土著人民要么被排除在分析之外，要么与其他种族和族裔身份合并为“其他”群体，这样的例子并不难找。将土著人民排除在外或进行合并，会阻碍我们以对集体行动有用的方式充分描述他们的健康状况。在这篇评论中，我们描述了与土著人民“小样本量”问题相关的统计效力（β）与结构和观念权力之间关系的三个不同但相关的问题：（i）数据获取和管理过程不足，（ii）规范性方法实践，以及（iii）科学交流不足。本着学科反思和自我批评的精神，我们在一位作者先前发表的研究中识别并审视了这些问题的表现。然后，我们讨论并再次强调造成这些问题的重要历史和当代不公正制度，最后总结现有的有前景的研究和分析实践。鉴于处理数量众多群体健康问题的工具主导着教学和研究领域，我们必须朝着范式转变迈进，以全面为土著人民和其他“数量较少”群体提供公平、正义和福祉。
