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Record W1526362886 · doi:10.1177/009885881303900211

The Role of Private Law in the Control of Risks Associated with Tobacco Smoking: The Canadian Experience

2013· article· en· W1526362886 on OpenAlexaffabout
Lara Khoury, Marie-Eve Couture-Ménard, О. Yu. Redko

Bibliographic record

VenueAmerican Journal of Law & Medicine · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsUniversité de SherbrookeMcGill University
Fundersnot available
KeywordsConstitutionalityLegislationTobacco controlGovernment (linguistics)Class actionBusinessControl (management)Political scienceLawAction (physics)Public administrationPublic healthMedicineState (computer science)EconomicsSupreme courtManagement

Abstract

fetched live from OpenAlex

Can private law litigation serve as a tool for advancing public health objectives? With this contentious and oft-asked question in mind, we tackle Canada's recent tobacco litigation. This Article first presents critical commentary regarding various lawsuits waged against Canadian cigarette manufacturers by citizens acting as individuals or as parties to class action lawsuits. We then turn to analyze how Canada's provincial governments rely on targeted legislation to facilitate private law recourses for recouping the healthcare costs of treating tobacco-related diseases. We address challenges to the constitutionality of this type of legislation, as well as attempts by manufacturers to transfer responsibility to the federal government. Canadian litigation in this field is nothing like that of the United States with regards to both the volume and variety of its individual and class action litigation claims. This is also true with regard to the stage of advancement of governmental claims in Canada. Nevertheless, particularities of the Canadian context may provide interesting contrast with the situation in the United States.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.300
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.

Study designQualitative
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

Citations0
Published2013
Admission routes2
Has abstractyes

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