Research priorities for tobacco control in developing countries: a regional approach to a global consultative process
Bibliographic record
Abstract
OBJECTIVE: To develop regional tobacco control research agendas for developing countries through a consultative process. METHODS: Research for International Tobacco Control, located at the International Development Research Centre in Ottawa, Canada, convened three regional meetings for Latin America and the Caribbean, South and Southeast Asia, and Eastern, Central and Southern Africa. Participation by researchers, policymakers, and advocates from a wide range of disciplines ensured an accurate representation of regional issues. RESULTS: The four main recurring themes within each regional agenda were: (1) the lack of standardised and comparable data; (2) the absence of a network for communication of information, data, and best practices; (3) a lack of adequate capacity for tobacco control research, especially in non-health related areas such as economics and policy analysis; and (4) a need for concerted mobilisation of human and financial resources in order to implement a comprehensive research agenda, build partnerships, and stimulate comparative research and analysis. Specific research issues included the need for descriptive data with respect to the supply side of the tobacco equation, and analytical data related to tobacco use, production and marketing, and taxation. CONCLUSIONS: There was a uniform perception of tobacco as a multidisciplinary issue. All regional agendas included a balance of health, economic, agricultural, environmental, sociocultural, and international trade concerns. Research data are urgently required to provide a sound basis for the development of tobacco control policies and programmes. As tobacco control takes its rightful place on the global health agenda, it is vital that funding for tobacco control research be increased.
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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 | 0.288 | 0.149 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.027 | 0.016 |
| Open science | 0.007 | 0.034 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".