Are national policies on global health in fact national policies on global health governance? A comparison of policy designs from Norway and Switzerland
Bibliographic record
Abstract
BACKGROUND: Since the signing of the Oslo Ministerial Declaration in 2007, the idea that foreign policy formulation should include health considerations has gained traction on the United Nations agenda as evidenced by annual General Assembly resolutions on global health and foreign policy. The adoption of national policies on global health (NPGH) is one way that some member states integrate health and foreign policymaking. This paper explores what these policies intend to do and how countries plan to do it. METHODS: using Schneider and Ingram's policy design framework. After replicating analysis methods for each document, we analysed them side by side to explore the commonalities and differences across elements of NPGH design. RESULTS: Analyses indicate that NPGH expect to influence change outside their borders. Targeting the international level, they aim to affect policy venues, multilateral partnerships and international institutions. Instruments for supporting desired changes are primarily those of health diplomacy, proposed as a tool for negotiating interests and objectives for global health between multiple sectors, used internally in Switzerland and externally in Norway. CONCLUSION: Findings suggest that NPGH designs contribute to constructing the global health governance system by identifying it as a policy target, and policy instruments may elude the health sector actors unless implementation rules explicitly include them. Research should explore how future NPGH designs may construct different kinds of targets as politicised groups of actors on which national governments seek to exercise influence for global health decision-making.
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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 | 0.060 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".