USMCA (NAFTA 2.0): tightening the constraints on the right to regulate for public health
Bibliographic record
Abstract
Abstract Background In late 2018 the United States, Canada, and Mexico signed a new trade agreement (most commonly referred to by its US-centric acronym, the United States-Mexico-Canada Agreement, or USMCA) to replace the 1994 North American Free Trade Agreement (NAFTA). The new agreement is the first major trade treaty negotiated under the shadow of the Trump Administration’s unilateral imposition of tariffs to pressure other countries to accept provisions more favourable to protectionist US economic interests. Although not yet ratified, the agreement is widely seen as indicative of how the US will engage in future international trade negotiations. Methods Drawing from methods used in earlier health impact assessments of the Trans-Pacific Partnership agreement, we undertook a detailed analysis of USMCA chapters that have direct or indirect implications for health. We began with an initial reading of the entire agreement, followed by multiple line-by-line readings of key chapters. Secondary sources and inter-rater (comparative) analyses by the four authors were used to ensure rigour in our assessments. Results The USMCA expands intellectual property rights and regulatory constraints that will lead to increased drug costs, particularly in Canada and Mexico. It opens up markets in both Canada and Mexico for US food exports without reducing the subsidies the US provides to its own producers, and introduces a number of new regulatory reforms that weaken public health oversight of food safety. It reduces regulatory policy space through new provisions on ‘technical barriers to trade’ and requirements for greater regulatory coherence and harmonization across the three countries. It puts some limitations on contentious investor-state dispute provisions between the US and Mexico, provisions often used to challenge or chill health and environmental measures, and eliminates them completely in disputes between the US and Canada; but it allows for new ‘legacy claims’ for 3 years after the agreement enters into force. Its labour and environmental chapters contain a few improvements but overall do little to ensure either workers’ rights or environmental protection. Conclusion Rather than enhancing public health protection the USMCA places new, extended, and enforceable obligations on public regulators that increase the power (voice) of corporate (investor) interests during the development of new regulations. It is not a health-enhancing template for future trade agreements that governments should emulate.
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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 | 0.034 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".