The Troubled Dream of Genetic Medicine: Ethnicity and Innovation in Tay-Sachs, Cystic Fibrosis, and Sickle Cell Disease
Keith Wailoo, Stephen Pemberton
Winner of the History of Science category of the Professional and Scholarly Publishing Awards given by the Association of American Publishers Why do racial and ethnic controversies become attached, as they often do, to discussions of modern genetics? How do theories about genetic difference become entangled with political debates about cultural and group differences in America? Such issues are a conspicuous part of the histories of three hereditary diseases: Tay-Sachs, commonly identified with Jewish Americans; cystic fibrosis, often labeled a "Caucasian" disease; and sickle cell disease, widely associated with African Americans. In this captivating account, historians Keith Wailoo and Stephen Pemberton reveal how these diseases—fraught with ethnic and racial meanings for many Americans—became objects of biological fascination and crucibles of social debate. Peering behind the headlines of breakthrough treatments and coming cures, they tell a complex story: about different kinds of suffering and faith, about unequal access to the promises and perils of modern medicine, and about how Americans consume innovation and how they come to believe in, or resist, the notion of imminent medical breakthroughs.
Award History
1 wins · 1 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| PROSE Award for History of Science, Medicine, and Technology | 2006 | Winner | Official source |
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01 Central figures
None extracted with sufficient confidence.
02 Central places
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03 Suggested argument
Racial and ethnic controversies attach to modern genetics because theories of genetic difference become entangled with U.S. political debates about cultural and group differences through the histories of hereditary diseases.
Model confidence 78%
04 Reading orientation
70 / 100 academicAcademic
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 74%.