The EU-Canada Free Trade Agreement: What is on the Table for Agriculture?
Bibliographic record
Abstract
In October 2008 French President Nicholas Sarkozy and Canadian Prime Minister Stephen Harper announced that the EU and Canada would seek a free trade agreement and in May 2009 negotiations on a Comprehensive Economic and Trade Agreement (CETA) commenced. There have been a number of negotiating sessions since then and good progress has been reported. One of the more difficult sectors was expected to be agriculture. This paper outlines the major opportunities for expanded agricultural trade between the EU and Canada as well as those areas where the negotiations are expected to be particularly difficult. Topics include, subsidies, sanitary and phytosanitary barriers to trade, tariffs, tariff line adjustments, regulatory harmonization, protection for geographical indications, barriers to trade in genetically modified products and TRQs in the Canadian dairy sector. A section on opportunities and concerns of particular interest to the agri-food sector of the UK is included. The paper concludes with a discussion of the expected outcome and degree of trade expansion that will follow a successful conclusion to the negotiations.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.027 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".