How much of the Transpacific Partnership is in the United States-Mexico-Canada Agreement?
Bibliographic record
Abstract
The United States-Mexico-Canada Agreement (USMCA) provided the first opportunity for the Trump administration to translate its “America First” trade policy into specific treaty design. In this article, we evaluate how radical these changes have been by systematically comparing the USMCA to its predecessors. We find that, first, the USMCA copies 57 percent of its text from the Transpacific Partnership (TPP), which Trump had repudiated and unsigned once he took office. Compared to U.S. treaty practice generally, the USCMA is more of a continuation rather than a departure from prior texts. Second, we systematically investigate where the USMCA diverges from the TPP. We find that USMCA treaty design differences can be grouped in five categories: (1) structural remnants of NAFTA, such as bi-national panels to review trade remedies; (2) “America First” elements, such as tighter rules of origins; (3) modernizations, e.g. by incorporating TPP innovations on digital trade; (4) additions on non-U.S. policy priorities, such as gender rights, promoted by the other USMCA states; and finally (5) changes of a more technical nature. In sum, contrary to Trump’s rhetoric, the USMCA does not usher in a new generation of trade agreements, but it does engage in targeted innovations that are driven by varying policy considerations that include but are not limited to his “America First” agenda.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".