The Expanding Labor Dimension of US-Negotiated Regional Trade Agreements: TPP and USMCA
Bibliographic record
Abstract
During the past several years, the US government has negotiated two regional trade agreements with far reaching labor provisions — the Trans-Pacific Partnership (TPP) and the United States-Mexico-Canada Agreement (USMCA). Signed in early 2016, the TPP labor chapter enhances second-generation worker rights in several significant ways: First, the TPP obligates each party to "adopt and maintain" statutes, regulations, and practices governing acceptable conditions of work with respect to minimum wages, hours of work, and occupational safety and health, as determined by that party. Second, the obligation not to waive or derogate from fundamental labor rights or conditions of work is specifically applied to special trade or customs areas such as export processing zones (EPZs). Third, the TPP obligates each government to "discourage, through initiatives it considers appropriate" the importation of goods produced by forced or compulsory labor. Signed in 2019, the USMCA contains numerous labor obligations for the United States. (These US obligations extend only to the federal level, not to the state level.) Under the USMCA labor chapter, Mexico and Canada would be able to bring cases against the US for violations of the labor rights set out in USMCA. The prospect of establishing US accountability is important because although complaints against the US are sometimes brought in the supervisory mechanisms of the International Labour Organization (ILO), when the ILO finds a US violation, the ILO has no enforcement mechanism against the US. In contrast, the USMCA would give Mexico or Canada an enforcement mechanism to levy trade sanctions against the US should the US be found to be out of compliance with the USMCA and to fail to correct that violation.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".