The institutional design of CUSMA: Improvement or reversal vis-à-vis NAFTA?
Bibliographic record
Abstract
In this article we comparatively analyze the institutional design of the 2020 Canada-United States-Mexico Agreement (CUSMA) vis-à-vis the 1994 North American Free Trade Agreement (NAFTA). In the modernization of NAFTA into CUSMA, three strategies were employed: updating, upgrading, and adjusting the institutional design. We explore whether the implementation of these strategies provide a better governance of free trade and investment in the region compared to NAFTA. To do so, we conduct an in-depth evaluation of both agreements. Our central argument is that there were both progress and reversals in several areas: for example, the strength and powers of dispute settlement mechanisms, an improvement in the implementation of the working groups, changes in the flexibility or rigidity of its architecture depending on the sector analyzed, among many others. The article is comprised of three sections, each of them dealing with one of the three strategies under scrutiny. Finally, based on the central findings, we provide some public policy recommendations to strengthen the governance of free trade and investment in North America through the CUSMA.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".