Impact assessment of the WHO FCTC over its first decade: methodology of the expert group
Bibliographic record
Abstract
BACKGROUND: At its sixth meeting (Moscow, November 2014), the Conference of the Parties (COP) adopted decision FCTC/COP6(13) that called for an impact assessment to 'examine the impact of the WHO Framework Convention on Tobacco Control (FCTC) on the implementation of tobacco control measures and on the effectiveness of its implementation' after its first 10 years. An independent expert group (EG) was established to conduct the impact assessment, and report their findings at COP7 (Delhi, November 2016). This article describes the methodology used by the EG to conduct the first comprehensive multi-method assessment of the possible causal impact of the FCTC on global tobacco control over the past decade. METHODS: The EG developed and followed a four-stage process model to conduct the impact assessment: (1) desk review of literature on FCTC impact; (2) collection and analysis of interview data from 12 country missions; (3) data synthesis and interpretation; and (4) preparation of a final report. CONCLUSIONS: The EG developed and engaged in a transparent and systematic process to conduct the FCTC impact assessment. The methods employed were rigorous, and explicitly guided by concerns about the difficulty of ascribing cause-and-effect relations. The EG's report and supporting documents represent important sources of the positive impact of the Convention over its first decade. As development of the FCTC increasingly shifts to mechanisms for accelerating global implementation, the EG's process model can be used as a methodology to assist Parties in carrying out their own assessments of the impact of the Treaty.
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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 | 0.327 | 0.238 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".