Comparison of tobacco control programs worldwide: A quantitative analysis of the 2015 World Health Organization MPOWER report
Bibliographic record
Abstract
BACKGROUND: A report of the activities of countries worldwide for six main policies to control tobacco use is published once every 2 years by the World Health Organization (WHO). Our objective was to perform a quantitative analysis for it in countries and regions to make a simple view of its programs. METHODS: This was a cross-sectional study by filling out a validated checklist from the 2015 WHO Report (MPOWER). All ten MPOWER measures got scores and were entered independently by two individuals and a third party compared the values. RESULTS: Fifteen countries, which acquired the highest scores (85% of total 37), included Panama and Turkey with 35, Brazil and Uruguay with 34, Ireland, United Kingdom, Iran, Brunei, Argentina, and Costa Rica with 33, and Australia, Nepal, Thailand, Canada, and Mauritius with 32 points. CONCLUSIONS: Comparison of scores of different countries in this respect can be beneficial since it creates a challenge for the health policymakers to find weakness of the tobacco control programs to work on it.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".