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Record W2802442146

Food as a Dangerous Product: The Promise of Private Law for Public Health

2017· dissertation· en· W2802442146 on OpenAlexfundaboutno aff
Jacob Shelley

Bibliographic record

VenueTSpace (University of Toronto) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsnot available
FundersSt. Jude MedicalCanadian Institutes of Health ResearchFraser Health Authority
KeywordsPublic healthBusinessProduct (mathematics)LawPublic health lawEnvironmental healthPolitical scienceMedicineHealth careHealth policyPublic health policyMathematics
DOInot available

Abstract

fetched live from OpenAlex

Obesity and diet-related chronic diseases are a critical public health problem facing Canadians. Interventions aimed at improving diet and the overall food environment have had limited success, and as a consequence, many have suggested an increased use of legal tools, including litigation. This project examines the potential of the duty to warn, part of product liability law, as a strategy for addressing obesity and other diet-related chronic diseases.\nTo this end, the project proceeds in two parts. Part one project examines the potential of tort law to be used to address public health problems. It begins by establishing the congruence between tort law and public health, and suggests that there are potential benefits of public health litigation for obesity prevention. This sets the foundation for part two, which argues that Canadian jurisprudence clearly establishes that food manufacturers have a duty to warn consumers about the risks associated with consuming food products. Part two examines key aspects of a tort claim based on a failure to warn, namely, the duty of care, standard of care, and factual causation. It sets out an approach to failure to warn cases that is consistent with general principles of negligence law, but that is sensitive to the particularities of a failure to warn case.\nThis project establishes that food manufactures are required to provide warnings that are consistent with the standards of adequacy as set out by the Ontario Court of Appeal decision in Buchan v Ortho Pharmaceutical. Buchan, which has been affirmed by the Supreme Court of Canada, sets out explicit criteria for determining adequacy, including prohibitions against collateral efforts to negate or neutralize warnings. It is clear that food manufacturers are neither fulfilling their obligation to provide warnings nor adhering to the Buchan standard. This project concludes that food manufacturers should be held accountable for this failure.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
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 head0.048
GPT teacher head0.318
Teacher spread0.270 · 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 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

Citations0
Published2017
Admission routes2
Has abstractyes

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