Do trade agreements substantially limit development of local / sustainable food systems in Canada?
Bibliographic record
Abstract
A common view in policy and business circles is that certain elements of trade agreements (General Agreement on Tariff and Trade rules, the World Trade Organization Agreement on Agriculture, and the North American Free Trade Agreement) and the Canadian Agreement on Internal Trade significantly limit the policy and program instruments available to support the development of local/sustainable food systems. This exploratory textual analysis of select trade articles, filtered through a local/sustainable lens, suggests that Canadian governments can put in place more substantial policy and program drivers without triggering trade disputes. Of particular note is that local/sustainable foods may not be considered equivalent to imported conventional ones, and therefore many provisions of the trade agreements may not be applicable. Equally important, the rules do permit certain kinds of support, there are numerous exemptions and thresholds for application of measures, and many current actors in local/sustainable implementation may not be subject to the agreements. Based on this textual analysis, pertinent instrument design features are proposed that would allow governments and other parties to support local/sustainable food systems without triggering trade disputes.
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".