Towards a coherent global framework for health financing: recommendations and recent developments
Bibliographic record
Abstract
The articles in this special issue have demonstrated how unprecedented transitions have come with both challenges and opportunities for health financing. Against the background of these challenges and opportunities, the Working Group on Health Financing at the Chatham House Centre on Global Health Security laid out, in 2014, a set of policy responses encapsulated in 20 recommendations for how to make progress towards a coherent global framework for health financing. These recommendations pertain to domestic financing of national health systems, global public goods for health, external financing for national health systems and the cross-cutting issues of accountability and agreement on a new global framework. Since the Working Group concluded its work, multiple events have reinforced the group's recommendations. Among these are the agreement on the Addis Ababa Action Agenda, the adoption of the Sustainable Development Goals, the outbreak of Ebola in West Africa and the release of the Panama Papers. These events also represent new stepping stones towards a new global framework.
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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 | 0.083 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.032 | 0.043 |
| Open science | 0.008 | 0.015 |
| Research integrity | 0.054 | 0.041 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".