Realist evaluation of the role of the Universal Health Coverage Partnership in strengthening policy dialogue for health planning and financing: a protocol
Bibliographic record
Abstract
INTRODUCTION: In 2011, WHO, the European Union and Luxembourg entered into a collaborative agreement to support policy dialogue for health planning and financing; these were acknowledged as core areas in need of targeted support in countries' quest towards universal health coverage (UHC). Entitled 'Universal Health Coverage Partnership', this intervention is intended to strengthen countries' capacity to develop, negotiate, implement, monitor and evaluate robust and integrated national health policies oriented towards UHC. It is a complex intervention involving a multitude of actors working on a significant number of remarkably diverse activities in different countries. METHODS AND ANALYSIS: The researchers will conduct a realist evaluation to answer the following question: How, in what contexts, and triggering what mechanisms, does the Partnership support policy dialogue for health planning and financing towards UHC? A qualitative multiple case study will be undertaken in Togo, Liberia, Democratic Republic of Congo, Cape Verde, Burkina Faso and Niger. Three steps will be implemented: (1) formulating context-mechanism-outcome explanatory propositions to guide data collection, based on expert knowledge and theoretical literature; (2) collecting empirical data through semistructured interviews with key informants and observations of key events, and analysing data; (3) specifying the intervention theory. ETHICS AND DISSEMINATION: The primary target audiences are WHO and its partner countries; international and national stakeholders involved in or supporting policy dialogues in the health sector, especially in low-income countries; and researchers with interest in UHC, policy dialogue, evaluation research and/or realist evaluation.
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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 | 0.242 | 0.170 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.055 | 0.008 |
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".