International Trade: Partners, Politics, and Promises: An Analysis of the North American Free Trade Agreement's Arbitral Panel Decision concerning the United States-Mexico Trucking Dispute
Bibliographic record
Abstract
The North American Free Trade Agreement (NAFTA)' has been called "the most comprehensive trade agreement ever negotiated which creates the world's largest integrated market for goods and services." 2 NAFTA provides the three signing parties, the United States, Mexico, and Canada, various methods for resolving disputes.3 Mexico and the United States have been disputing NAFTA obligations concerning cross-border trucking services for several years.The dispute arises out of the refusal by the United States to allow the Mexican trucking service industry authority to operate within U.S. borders, although NAFTA provides that such services shall be permitted.'Mexico requested the formation of an arbitral panel, and that panel held in Cross-Border Trucking that the United States was in violation of several provisions of NAFTA.6 This Note provides a brief historical synopsis of NAFTA in relation to the U.S.-Mexico trucking dispute and examines the panel's rationale in rendering its decision.Next, this Note discusses the implications of the panel's decision and the reaction of the United States to the decision.* Class of 2003, University of New Mexico School of Law.Special thank you to Professor Franklin Gill for his guidance, knowledge, and motivation while supervising my progression throughout the development of this Note.1.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| 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".