Bibliographic record
Abstract
This article examines Canada’s trade policy in light of efforts by the Harper government to respond to increasing global competition through the Global Markets Action Plan (2013). Through an analysis of three initiatives, the Canada–Korea Free Trade Agreement (CKFTA), the Canada–European Union Comprehensive Economic Trade Agreement (CETA), and the Trans–Pacific Partnership (TPP), it becomes clear that Canada’s current strategy has only gone part of the way to enact policies that will be most beneficial to its economy. This article shows that Canada’s Global Markets Action Plan, though ambitious, does not correctly prioritize Canada’s interests: it gives too little attention to improving Canada’s strongest trading relationship with its immediate neighbors in North America; it does not comprehensively address the changing nature of trade (which is now focused on trade in value-added products); and finally, its almost singular focus on market access and increasing exports directs attention away from the type of liberalization that would be most beneficial to Canadians, which is opening up the market for imports and dismantling Canada’s supply management system.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 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".