Food as a Dangerous Product: The Promise of Private Law for Public Health
Bibliographic record
Abstract
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. To 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. This 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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.043 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.025 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".