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Is doing better science enough?: An autoethnographic study of a multidisciplinary collaboration to measure structural racism
Journal article   Open access   Peer reviewed

Is doing better science enough?: An autoethnographic study of a multidisciplinary collaboration to measure structural racism

Paris B Adkins-Jackson, Emily A Haozous, Boeun Kim, Alicia Cooke, Melissa D Hladek, Darnell Leatherwood, Tiffany Riser, Odis Johnson, Erik Westlund, Laura J Samuel, …
Ethnicity & health
09/08/2026
DOI: 10.1080/13557858.2026.2729315
PMID: 42710845
url
https://doi.org/10.1080/13557858.2026.2729315View
Published (Version of record) Open Access

Abstract

Addressing structural racism remains a critical challenge in population health and social sciences, as traditional quantitative approaches often fail to disrupt long-standing racialized health hierarchies. This study critically interrogates the process of a multidisciplinary scientific collaboration attempting to operationalize and measure life course structural racism while enacting an anti-racist praxis. Utilizing a collaborative analytic autoethnography framework grounded in social cognitive theory and anti-racist praxis, our team - comprising biostatisticians, nurse scientists, epidemiologists, gerontologists, social scientists, and a nephrologist across racialized groups, career stages, and institutions - treated our team process as a socio-analytical field site. We examined the tension between individualistic paradigms and systemic measurement, gathering qualitative field data from team deliberations, and a dedicated focus group. Three primary autoethnographic themes emerged: operationalizing and understanding structural racism, constructing methodological infrastructure, and navigating accountability and the pursuit of a multidimensional measure. While qualitative life-course history interviews, expert panels, public podcasts, and a national survey advanced conceptual and data infrastructure, significant methodological barriers - including historical address recall, geocoding missingness, and geographic mismatch - prevented immediate measure validation. Autoethnographic reflection revealed how institutional incentives, capitalistic academic pressures, and funding mechanisms complicate collective equity work. By interrogating our collaborative process, we demonstrate that doing 'different science' requires prioritizing reflexive, collective team dynamics and infrastructure over rapid measure production. Embedding anti-racist praxis and community accountability into scientific collaborations offers a transformative pathway for advancing structural racism research and dismantling systemic health inequities.
SDH 17: Partnerships for the goals collaborative autoethnography anti-racist praxis population health infrastructure SDG 11: Sustainable cities and communities Structural racism multidisciplinary collaboration health equity SDG 16: Peace, justice, and strong institutions

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