Global governance and the broader determinants of health: A comparative case study of UNDP’s and WTO’s engagement with global health
Bibliographic record
Abstract
This comparative case study investigated how two intergovernmental organisations without formal health mandates - the United Nations Development Programme (UNDP) and the World Trade Organization (WTO) - have engaged with global health issues. Triangulating insights from key institutional documents, ten semi-structured interviews with senior officials, and scholarly books tracing the history of both organisations, the study identified an evolving and broadened engagement with global health issues in UNDP and WTO. Within WTO, the dominant view was that enhancing international trade is instrumental to improving global health, although the need to resolve tensions between public health objectives and WTO agreements was recognised. For UNDP, interviewees reported that the agency gained prominence in global health for its response to HIV/AIDS in the 1990s and early 2000s. Learning from that experience, the agency has evolved and expanded its role in two respects: it has increasingly facilitated processes to provide global normative direction for global health issues such as HIV/AIDS and access to medicines, and it has expanded its focus beyond HIV/AIDS. Overall, the study findings suggest the need for seeking greater integration among international institutions, closing key global institutional gaps, and establishing a shared global institutional space for promoting action on the broader determinants of health.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".