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The Pitfalls of Genomic Data Diversity

Biomedical research recruitment today focuses on including participants representative of global genetic variation—rightfully so. But ethnographic attention to practices of inclusion highlights how this agenda often transforms into “predatory inclusion,” simplistic pushes to get Black and brown peop...

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Detalles Bibliográficos
Autores principales: Jabloner, Anna, Walker, Alexis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655895/
https://www.ncbi.nlm.nih.gov/pubmed/37963133
http://dx.doi.org/10.1002/hast.1511
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author Jabloner, Anna
Walker, Alexis
author_facet Jabloner, Anna
Walker, Alexis
author_sort Jabloner, Anna
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description Biomedical research recruitment today focuses on including participants representative of global genetic variation—rightfully so. But ethnographic attention to practices of inclusion highlights how this agenda often transforms into “predatory inclusion,” simplistic pushes to get Black and brown people into genomic databases. As anthropologists of medicine, we argue that the question of how to get from diverse data to concrete benefit for people who are marginalized cannot be presumed to work itself out as a byproduct of diverse datasets. To actualize the equitable translation of genomics, practitioners need to place the impacts of ancestral genetic difference in the scope of much more impactful social determinants. For this to happen, multidisciplinary expertise needs to be leveraged, and current, structurally unequal health care systems ultimately need to transform. As modest steps toward this goal, new models for benefit‐sharing must be developed and implemented to mitigate existing inequality between data donors and the entities profiting from that data.
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spelling pubmed-106558952023-11-17 The Pitfalls of Genomic Data Diversity Jabloner, Anna Walker, Alexis Hastings Cent Rep Essays Biomedical research recruitment today focuses on including participants representative of global genetic variation—rightfully so. But ethnographic attention to practices of inclusion highlights how this agenda often transforms into “predatory inclusion,” simplistic pushes to get Black and brown people into genomic databases. As anthropologists of medicine, we argue that the question of how to get from diverse data to concrete benefit for people who are marginalized cannot be presumed to work itself out as a byproduct of diverse datasets. To actualize the equitable translation of genomics, practitioners need to place the impacts of ancestral genetic difference in the scope of much more impactful social determinants. For this to happen, multidisciplinary expertise needs to be leveraged, and current, structurally unequal health care systems ultimately need to transform. As modest steps toward this goal, new models for benefit‐sharing must be developed and implemented to mitigate existing inequality between data donors and the entities profiting from that data. John Wiley and Sons Inc. 2023-11-14 2023 /pmc/articles/PMC10655895/ /pubmed/37963133 http://dx.doi.org/10.1002/hast.1511 Text en © 2023 The Authors. Hastings Center Report published by Wiley Periodicals LLC on behalf of The Hastings Center. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Essays
Jabloner, Anna
Walker, Alexis
The Pitfalls of Genomic Data Diversity
title The Pitfalls of Genomic Data Diversity
title_full The Pitfalls of Genomic Data Diversity
title_fullStr The Pitfalls of Genomic Data Diversity
title_full_unstemmed The Pitfalls of Genomic Data Diversity
title_short The Pitfalls of Genomic Data Diversity
title_sort pitfalls of genomic data diversity
topic Essays
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655895/
https://www.ncbi.nlm.nih.gov/pubmed/37963133
http://dx.doi.org/10.1002/hast.1511
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