Impact of the WHO FCTC over the first decade: a global evidence review prepared for the Impact Assessment Expert Group
Bibliographic record
Abstract
OBJECTIVE: To present findings of a narrative review on the implementation and effectiveness of 17 Articles of the WHO Framework Convention on Tobacco Control (FCTC) during the Treaty's first decade. DATA SOURCES: Published reports on global FCTC implementation; searches of four databases through June 2016; hand-search of publications/online resources; tobacco control experts. STUDY SELECTION: WHO Convention Secretariat global progress reports (2010, 2012, 2014); 2015 WHO report on the global tobacco epidemic; studies of social, behavioural, health, economic and/or environmental impacts of FCTC policies. DATA EXTRACTION: Progress in the implementation of 17 FCTC Articles was categorised (higher/intermediate/lower) by consensus. 128 studies were independently selected by multiple authors in consultation with experts. DATA SYNTHESIS: Implementation was highest for smoke-free laws, health warnings and education campaigns, youth access laws, and reporting/information exchange, and lowest for measures to counter industry interference, regulate tobacco product contents, promote alternative livelihoods and protect health/environment. Price/tax increases, comprehensive smoking and marketing bans, health warnings, and cessation treatment are associated with decreased tobacco consumption/health risks and increased quitting. Mass media campaigns and youth access laws prevent smoking initiation, decrease prevalence and promote cessation. There were few studies on the effectiveness of policies in several domains, including measures to prevent industry interference and regulate tobacco product contents. CONCLUSIONS: The FCTC has increased the implementation of measures across several policy domains, and these implementations have resulted in measurable impacts on tobacco consumption, prevalence and other outcomes. However, FCTC implementation must be accelerated, and Parties need to meet all their Treaty obligations and consider measures that exceed minimum requirements.
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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 | 0.075 | 0.169 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".