Food for thought: How trade agreements impact the prospects for a national food policy
Bibliographic record
Abstract
This article examines the prospect for a national food policy through the lens of trade agreements and the concept of policy space. It traces the shrinking of domestic policy space in recent decades as a result of trade agreements. Advocates such as Food Secure Canada seek a “coherent” food policy that supports a sustainable, more domestically-focused, food system. This article argues that the prospects for such a policy are constrained, based on Canada’s past history, under both Liberal and Conservative governments, as well as recent bilateral and regional agreements. It examines the Canada-European Union Comprehensive Economic and Trade Agreement (CETA), the Transpacific Partnership Agreement (TPP) which included the United States, and the subsequent Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) negotiated by the remaining eleven partners after the US departure. Focussing on market access, standards, regulatory harmonization and procurement, I argue that provisions in these agreements, along with what we might expect in future trade negotiations, pose challenges for the development of a national food policy.
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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.020 | 0.035 |
| Scholarly communication | 0.033 | 0.016 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 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".