Shared decision-making in cardiac care: can we close the gap between good intentions and improved outcomes?
Bibliographic record
Abstract
<h3>Objective</h3> Small Island Developing States (SIDS) struggle with implementing multisectoral tobacco control measures, and health sector actors often lack capacity to forge multisectoral commitment. This study aims to explore the sources and dynamics of authority that can enable multisectoral collaboration despite the divergence of policy agendas in tobacco control. <h3>Methods</h3> We applied a qualitative, explorative case study design, with data collection and analysis guided by an analytical framework that identifies sources and dynamics of authority. Seventy interviews were conducted in Fiji and Vanuatu between 2018 and 2019. <h3>Results</h3> The key features shaping multisectoral coordination for tobacco control in Fiji and Vanuatu are the expert, institutional, capacity-based and legal authority that state and non-state actors have in tobacco governance. The amount of authority actors can secure from these sources was shown to be influenced by their performance (perceived or real), the discourse around tobacco control, the existing legal tools and their strategic alliances. SIDS vulnerabilities, arising from small size, isolation and developing economies, facilitate an economic growth discourse that reduces health sector actors’ authority and empowers protobacco actors to drive tobacco governance. <h3>Conclusions</h3> Our results highlight the need for terms of engagement with the tobacco industry to enable governments to implement multisectoral tobacco control measures. Expanding assistance on tobacco control among government and civil society actors and increasing messaging about the impact of economic, trade and agricultural practices on health are essential to help SIDS implement the Framework Convention on Tobacco Control.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".