An Analysis of Fair Use and GIs in the Transition from NAFTA to USMCA
Bibliographic record
Abstract
The North-American Free Trade Agreement (NAFTA) was recently superseded by the United States-Mexico-Canada Agreement (USMCA). The first agreement between the three countries was signed three decades ago and it meant the first-time inclusion of a whole chapter about intellectual property (IP) in a Free Trade Agreement (FTA). The practice has become common in the current panorama of intellectual property, where international free trade agreements are prolific. Patent law is the area which has shown the greater degrees of harmonization, but other topics are the ones that are attracting attention, because of the different opinions that exist in contracting countries. Two intellectual property areas were selected for analysis in this work, with the objective of identifying the missed opportunities for international IP protection in the renegotiation of the NAFTA agreement vis-a-vis the stances of the contracting parties and their IP tradition. The first one is the limitations and exceptions for copyright’s exclusive rights. The second one is the recognition and protection of geographical indications. The thesis presents an analysis of the problematics of such an attempt, considering the different approaches, priorities and intentions of each of the countries. It also explores the possible opportunities for future FTAs to implement specific IP provisions in those two areas, where the contracting parties have different opinions on the ideal solution for balancing the interests of the right-holders and the public interest.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".