NAFTA Termination: Legal Process in Canada and Mexico
Bibliographic record
Abstract
The mechanics of US withdrawal from the North American Free Trade Agreement (NAFTA) have been widely explored, with an emerging consensus among legal experts that President Donald Trump does have the authority to pull out of the accord. This Policy Brief examines the legal procedures in Canada and Mexico in the event that either country decides to withdraw or terminate NAFTA. Relative to the United States, Canada and Mexico have clearer legal procedures. To terminate NAFTA in Canada, the Department of International Trade would send the notice to withdrawal upon approval by the Cabinet and the Order in Council. In Mexico, the president can notify withdrawal from NAFTA under Article 2205, following Senate approval. To raise tariffs to the MFN level, Canada requires amendment of federal statutes that requires passage in both chambers of the Parliament through regular procedures. To raise its tariffs, Mexico requires a bill to amend federal legislation that has the approval of the Senate and the Chamber of Deputies. While the legal powers to withdraw from NAFTA commitments are very broad in all three partner countries, political and economic constraints greatly narrow the scope of action. Canada conducts about 64 percent of its two-way merchandise trade with the United States; the figure for Mexico is 63 percent; and the United States depends on Canada and Mexico for 29 percent of its global commerce.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.035 | 0.009 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".