Anthropological Engagements with Global Health
Bibliographic record
Abstract
Epidemic infectious diseases like HIV/AIDS, tuberculosis, Ebola, and more recently COVID-19, have persistent and devastating impacts in human populations across the globe. In this Review essay, we consider together the monographs Epidemic Illusions (Richardson 2021) and Fevers, Feuds, and Diamonds (Farmer 2020), as well as the documentary film Bending the Arc (Davidson and Kos 2017), Together, they demonstrate the history of transnational colonialism, the significance of structural violence as a contributor to global health inequity, and the increasing presence of co-occurring epidemics worldwide, topics which are often absent from discussions of global health systems. These three works discuss epidemics as pathologies of history and sociocultural patterns of colonial dispossession in global health systems; the inclusion of patient narratives in two of them, the film Bending the Arc and the book Fevers, Feuds, and Diamonds, is pivotal in describing the intricacies of HIV infection and other infectious diseases, as well as the complexity of gaining control of syndemic diseases. Further, these three materials point to the importance of health education in communities and of access to healthcare by community members, and to the roles that health education and access play in health policy implementation.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.071 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".