Proceed with Precaution: The Statutory, Legal, and Consumer Influence on Genetically Modified Foods in Canada
Bibliographic record
Abstract
Despite the majority of consumers’ health and environmental concerns, genetically modified organisms (GMOs) now form a regular part of Canadian society. Our system of regulatory approval introduces GMOs into agriculture, while our legal regimes deal with rights and responsibilities with respect to GMO, all while grocers and consumers sell, buy and eat genetically modified foods (GMFs) as part of their daily diet. With the increasing prominence of GMOs in our society, and the consistent debate over their safety, there is a need to inject precaution into the principles behind how these foods and crops enter, remain and spread in the Canadian market. This paper describes and assesses both the Canadian regulatory scheme for GMOs and the intellectual property regimes that assign rights and shape competing claims in GMOs. Furthermore, it provides insight into the consumer’s voice on the debate over GMOs in society. This paper takes the view that there is a need for a precautionary approach to the regulation, control and spread of GMOs in Canada.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.036 | 0.020 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".