Global Health Diplomacy (GHD) and the integration of health into foreign policy: Towards a conceptual approach
Bibliographic record
Abstract
Since the end of the Cold War, health has gone from a peripheral concern in foreign policy negotiations to a prominent place on the global political agenda. While the rise of health onto the foreign policy agenda is by now old news, the driving forces behind its expansion into new political spheres remain understudied and undertheorized. This article builds on empirical findings from a four-country study of the integration of health into foreign policy, and proposes a conceptual approach to GHD to improve understanding of the conditions under which health is successfully positioned on the foreign policy agenda. Our approach consists of three dimensions: features of institutions and the interest various actors represent in GHD; the ideational environment in which GHD operates; and issue characteristics of the specific health concern entering foreign policy. Within each dimension, we identify specific variables that, in combination, make up the explanatory power of the proposed approach. The proposed approach does not relate to, or build upon, a single social sciences, public health, or international relations (IR) theory, but can be seen as a heuristic device to identify dimensions and variables that may shape why certain health issues rise onto the foreign policy agenda.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.006 | 0.051 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".