The tobacco reduction targets act: a legislated phase out for combustible cigarettes
Bibliographic record
Abstract
Background and challenges to implementation The recent widespread marketing of alternative nicotine devices and heated tobacco products is heralded by some as a viable harm reduction strategy, and feared by others as a means of perpetuating the smoking epidemic. Missing from the often heated debate are proposals for ways to ensure that combustible products are removed from the market as these ´reduced risk´ products are introduced. Intervention or response In other markets involving such diverse consumer products as light bulbs, automobile fuel, refrigerators, the introduction of less harmful goods has been accompanied by requirements that the more harmful products are removed from the market. Such interventions have yet to be implemented for the manufactured cigarette or other combustible tobacco products. Regulatory approaches developed for these other goods are available as an ENDGAME tool for tobacco control, and prototype legislation developed for Canada illustrates one of many ways in which this can be done. Results and lessons learnt Much has been learned from how harmful products can be successfully phased out. The challenge remains to see how well these lessons can be applied to a proposed phase-out of combustible tobacco products. Conclusions and key recommendations Voluntary efforts by tobacco companies to remove combustible products from the market cannot be relied upon. Legislative approaches to remove the most harmful products from circulation can be developed as a next generation tobacco control measures.
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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 | 0.034 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.029 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".