Native American DNA

Tribal Belonging and the False Promise of Genetic Science

Hardcover, 256 pages

Published Aug. 31, 2013 by Univ Of Minnesota Press.

ISBN:
978-0-8166-6585-3
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Who is a Native American? And who gets to decide? From genealogists searching online for their ancestors to fortune hunters hoping for a slice of casino profits from wealthy tribes, the answers to these seemingly straightforward questions have profound ramifications. The rise of DNA testing has further complicated the issues and raised the stakes.

In Native American DNA, Kim TallBear shows how DNA testing is a powerful—and problematic—scientific process that is useful in determining close biological relatives. But tribal membership is a legal category that has developed in dependence on certain social understandings and historical contexts, a set of concepts that entangles genetic information in a web of family relations, reservation histories, tribal rules, and government regulations. At a larger level, TallBear asserts, the “markers” that are identified and applied to specific groups such as Native American tribes bear the imprints of the cultural, racial, ethnic, national, and even …

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A Riveting Examination of the Science and Sociology of Genealogy, DNA Testing, and their interaction with Native Americans

Kim TallBear delivers a tour de force, eviscerating the "objectivity" of genetic testing (and science more broadly) and situating that mindset as it approaches the application of DNA testing to Native American populations. The careful consideration of what being a tribal member means, how it's fundamentally unrelated to genetics except in extremely limited situations, and how researchers have systematically recreated eugenic, racist categorizations (often unintentionally) is impressive and devastating. Importantly, this examination applies to DNA testing approaches for non-Native Americans as well - it just is fundamentally unequipped to answer questions of individual ancestry.

For anyone interested in the ethics and science of genetic testing this book is absolutely essential, but I would argue that anyone dealing with data analysis more broadly would benefit immensely from this book. Highly recommend

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