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Record W4311823692 · doi:10.26633/rpsp.2022.196

Moving in the right direction: tobacco packaging and labeling in the Americas

2022· article· en· W4311823692 on OpenAlexaboutno aff
Eric Crosbie, Olufemi Erinoso, Sara Perez, Ernesto M Sebrié

Bibliographic record

VenueRevista Panamericana de Salud Pública · 2022
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsTobacco controlPackaging and labelingBusinessConventionTobacco industryHarmAdvertisingHarm reductionMedicineEnvironmental healthLawMarketingPublic healthPolitical scienceNursing

Abstract

fetched live from OpenAlex

Objectives: To assess the adoption of tobacco packaging and labeling policies based on the World Health Organization (WHO) Framework Convention on Tobacco Control (FCTC)'s Article 11 guidelines, in the WHO Region of the Americas (AMRO). Methods: We reviewed tobacco control laws in AMRO from the Campaign for Tobacco-Free Kids' Tobacco Control Laws database. We analyzed four sub-policy areas for smoked and smokeless tobacco products: 1) health warning labels (HWLs), 2) constituents and emissions (C&Es), 3) misleading tobacco packaging and labeling, and 4) standardized "plain" packaging. Results: Of 35 countries in AMRO, 31 have tobacco packaging and labeling laws. Twenty-six countries require pictorial HWLs, 24 require warnings printed on at least 50% of the front and back of the packs, and 24 rotate a single or multiple (from 2 to 16) warnings within a specified period (from 5 up to 24 months). Only 21 countries require descriptive messages on toxic C&Es information. Twenty-seven countries ban brand descriptors with references to implied harm reduction (e.g., "light"), 24 ban figures, colors, and other signs, but only 13 prohibit emission yields printed on the packs. Only Canada and Uruguay have adopted standardized tobacco packaging while Uruguay also requires a single presentation (one brand variant) per brand family. Conclusion: Many countries in AMRO have made good progress in adopting multiple, rotating, large pictorial HWLs and banning misleading brand descriptors. However, there needs to be greater attention on other tobacco packaging and labeling provisions with a focus on implementing standardized tobacco packaging.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.301
Teacher spread0.281 · 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 teacher head, 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueRevista Panamericana de Salud PúblicaSame topicSmoking Behavior and CessationFrench-language works237,207