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Record W2156289071 · doi:10.1093/pubmed/fdv068

The role of public law-based litigation in tobacco companies’ strategies in high-income, FCTC ratifying countries, 2004–14

2015· article· en· W2156289071 on OpenAlexaboutno aff
Sarah Steele, Anna Gilmore, Martin McKee, David Stückler

Bibliographic record

VenueJournal of Public Health · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
FundersEconomic and Social Research CouncilWellcomeMedical Research CouncilNational Cancer InstituteNational Institutes of HealthWellcome Trust
KeywordsTobacco controlPublic healthBusinessTobacco industryControl (management)Political scienceLawEconomicsMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Tobacco companies use a host of strategies to undermine public health efforts directed to reduce and eliminate smoking. The success, failure and trends in domestic litigation used by tobacco companies to undermine tobacco control are not well understood, with commentators often assuming disputes are trade related or international in nature. We analyse domestic legal disputes involving tobacco companies and public health actors in high-income countries across the last decade to ascertain the types of action and the success or failure of cases, develop effective responses. METHODS: WorldLii, a publicly available online law repository, was used to identify domestic court cases involving tobacco companies from 2004 to 2014, while outcome data from LexisNexis and Westlaw databases were used to identify appeals and trace case history. RESULTS: We identified six domestic cases in the UK, Australia and Canada, noting that the tobacco industry won only one of six cases; a win later usurped by legislative reform and a further court case. Nevertheless, we found cases involve significant resource costs for governments, often progressing across multiple jurisdictional levels. DISCUSSION: We suggest that, in light of our results, while litigation takes up significant time and incurs legal costs for health ministries, policymakers must robustly fend off suggestions that litigation wastes taxpayers' money, pointing to the good prospects of winning such legal battles.

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)0.025
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
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 head0.075
GPT teacher head0.329
Teacher spread0.254 · 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 designNot applicable
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

Citations23
Published2015
Admission routes1
Has abstractyes

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