e-brief Stumbling Forward on Trade: The Doha Round, Free Trade Agreements, and Canada
Bibliographic record
Abstract
In recent years, the world has seen a proliferation of free trade agreements (FTAs) and, with the Doha Round on the rocks, the trend will likely continue.1 The flurry of newly ratified and potential US FTAs, notably with Australia and Korea, has been particularly worrisome for Canadians. Fears that Canada’s importance in US trade could dwindle, relegating Canada to a spoke on a US trading hub – a sentiment which helped bring about the Canada–US FTA and ultimately NAFTA – have re-emerged (Wonnacott 1990). These fears have brought calls to deepen North American integration (Robson 2007, Dymond and Hart 2008) and – the focus of this study – to expand Canada’s roster of FTA partners (Standing Committee on International Trade 2007).2 Indeed, in the past year, Canada’s federal government has initiated or negotiated trade agreements with numerous countries, including Colombia, Peru, and Korea and, most recently, the European Union. But before continuing headlong into the FTA game, Ottawa should pause to consider the effects of creating a web of FTAs. The decision to pursue FTAs should not be made lightly, because FTAs have the tendency to interfere with multilateral trade negotiations that potentially would deliver broader benefits (Limão 2006, Karacaovali and Limão 2008 and Adler 2007). How do they interfere? Countries ’ interests may shift away from global trade toward regional FTAs (Bhagwati 1991, 2008). The benefit a country derives from an FTA may cause it to approach multilateral trade negotiations with more I N
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.066 | 0.005 |
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".