The Edinburgh Companion to the Politics of American Health
Bibliographic record
Abstract
Examines the diverse, and often conflicted, political status of health in the United States from World War II to Covid-19. Explores the histories, cultures, policies and technologies of American health and medicine as they have developed over a 75-year period Brings together 45 experts from the US, Canada and the UK working across the fields of medicine, health policy, political and social history, political science, environmental studies, law, and cultural studies Uses the lenses of class, poverty, race, gender, sexuality and locality to study the concepts, policies and lived realities of U.S. healthcare and medical treatment Explores key controversies in American health, including global health and new technologies By emphasising the plurality of health experiences, and balancing national and transnational perspectives with the lived realities of diverse communities, this groundbreaking collection expands far beyond biomedical conceptions of health. Together, the contributors take a multi-layered view of the politics of US healthcare by examining it from historical, cultural, medical, sociological, legal, ethical and environmental perspectives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".