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Record W2101186265 · doi:10.1136/tc.10.4.364

Tobacco commerce on the internet: a threat to comprehensive tobacco control

2001· article· en· W2101186265 on OpenAlexaff
Joanna E Cohen, VIVIAN SARABIA, Mary Jane Ashley

Bibliographic record

VenueTobacco Control · 2001
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsOntario Tobacco Research UnitUniversity of Toronto
Fundersnot available
KeywordsTobacco controlThe InternetTobacco industryBusinessKey (lock)Promotion (chess)Control (management)AdvertisingTobacco in AlabamaState (computer science)MarketingTobacco harm reductionPolitical scienceMedicinePublic healthComputer securityEconomicsLawComputer science

Abstract

fetched live from OpenAlex

Although internet use continues to increase and e-commerce sales are expected to exceed US$1 trillion by the end of 2001, there have been few assessments in the literature regarding the implications of this medium for tobacco control efforts. This commentary explores the challenges that the internet may pose to the key components of a comprehensive tobacco control strategy, and pinpoints potential approaches for addressing these challenges. Four key challenges that the internet presents for tobacco control are identified: unrestricted sales to minors; cheaper cigarettes through tax avoidance and smuggling; unfettered advertising, marketing and promotion; and continued normalisation of the tobacco industry and its products. Potential strategies for addressing these challenges include international tobacco control agreements, national and state regulation, and legal remedies.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0060.006
Open science0.0020.002
Research integrity0.0200.013
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.038
GPT teacher head0.298
Teacher spread0.260 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations51
Published2001
Admission routes1
Has abstractyes

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