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Record W4396601359 · doi:10.1093/ntr/ntae108

The Tobacco Endgame: A Never-Ending Story?

2024· article· en· W4396601359 on OpenAlexaboutno aff
Alain Braillon, Adam Edward Lang

Bibliographic record

VenueNicotine & Tobacco Research · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsChess endgameSmoking preventionPsychologyMedicineSmoking cessationComputer science

Abstract

fetched live from OpenAlex

The report of the INSPIRED project aimed at providing insights into tobacco endgame goals deserved comment.1 First, the selection of six countries (Canada, Finland, Ireland, New Zealand, Scotland, and Sweden) is arbitrary. What about national plans that have flourished like fleeting flowers. For example, (1) in 2010, Bhutan imposed the world’s strictest law, a complete tobacco ban, but recently reversed it; (2) Russia, in 2017, was the first country to announce a generational ban but nothing happened.2 We are afraid that promises only bind those who believe in them. Second, tobacco policy is one public policy among many. On the form, political inaction or poor action usually prevails when it comes to implementation, regardless of promises. On the substance, none of the plans deserved the term “strategy” as balanced scorecard principles are ignored: no strategic management performance metrics to identify and improve the operations for achieving the outcomes. Second, why is it so difficult to acknowledge a gross failure? Certainly, the definition of the endgame can vary1 but we must confess that the core is a “tobacco-free generation.” However, no country has reduced nicotine content yet. Why is this key measure3 not yet among those recommended by the World Health Organization Framework Convention on Tobacco Control? On the contrary, many countries have allowed the marketing of new nicotine products by the tobacco industry, a bonanza allowing valuable investments.4 Robert West dared to blow the whistle: “The tobacco industry is not on the run … Globally its revenues continue to rise.”5 The consequences of the marketing of new nicotine products can hardly be a surprise. In Australia, a beacon for tobacco control, smoking prevalence in the general population has stopped decreasing and, for the first time since the early-to-mid-1990s, there is an increase in teen smoking.6 In England, although smoking rates in young people have been decreasing, more than 10% of 16–17-year-olds smoke, and smoking rates in teenagers have actually increased in some countries since 2020.7 At the population level, vaping is not an effective tool for getting rid of smoking. Electronic nicotine delivery systems end expectations for a tobacco endgame.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0130.022
Scholarly communication0.0160.033
Open science0.0040.012
Research integrity0.0340.048
Insufficient payload (model declined to judge)0.0090.004

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.

Opus teacher head0.105
GPT teacher head0.406
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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