Does Canada need trade adjustment assistance?
Bibliographic record
Abstract
Trade adjustment assistance (TAA) is government aid to those affected by trade agreements. We review the history of TAA in Canada and ask whether Canada needs to reintroduce it in response to the recent intensification of trade negotiations. In light of the compensation offered by the federal government in connection with the Canada–European Union Comprehensive Economic and Trade Agreement (CETA), we examine how TAA fits in with the evolution of Canadian federalism in the trade policy area. Based in part on interviews with provincial trade negotiators, we conclude, first, that the compensation is an outcome of Canadian federalism. Second, we argue that while there is no reason to reintroduce a federal TAA program for workers, compensation for provinces is necessary to facilitate their cooperation with the implementation of trade treaty provisions. Third, we suggest that a more transparent rationale for such compensation would be superior to the ad hoc compensation observed in CETA.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 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".