Analysing compliance of cigarette packaging with the FCTC and national legislation in eight former Soviet countries
Bibliographic record
Abstract
AIM: To analyse compliance of cigarette packets with the Framework Convention on Tobacco Control (FCTC) and national legislation and the policy actions that are required in eight former Soviet Union countries. METHODS: We obtained cigarette packets of each of the 10 most smoked cigarette brands in Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Moldova, Russia and Ukraine. The packets were then analysed using a standardised data collection instrument. The analysis included the placing, size and content of health warning labels and deceptive labels (eg, 'Lights'). Findings were assessed for compliance with the FCTC and national legislation. RESULTS: Health warnings were on all packets from all countries and met the FCTC minimum recommendations on size and position except Azerbaijan and Georgia. All countries used a variety of warnings except Azerbaijan. No country had pictorial health warnings, despite them being mandatory in Georgia and Moldova. All of the countries had deceptive labels despite being banned in all countries except Russia and Azerbaijan where still no such legislation exists. CONCLUSIONS: Despite progress in the use of health warning messages, gaps still remain-particularly with the use of deceptive labels. Stronger surveillance and enforcement mechanisms are required to improve compliance with the FCTC and national legislation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".