The USMCA as a Regional Integration Project
Bibliographic record
Abstract
This chapter argues that, albeit with variations, each of the three countries – that is, the US, Mexico and Canada – that belong to the USMCA can point to some concrete positive economic and welfare developments that have been realised because of NAFTA. The relative success of NAFTA / the USMCA has largely happened because of the belief that the three contracting parties have in the institution created to enhance the implementation of obligations under the agreement. Indeed, in 1994, NAFTA placed emphasis on the creation of ‘effective procedures for the implementation and application’ of member states’ obligations. In contrast to dispute settlement under the AfCFTA, ASEAN and MERCOSUR, a premium was placed on an effective dispute settlement mechanism. This explains why the USMCA’s chapter 10 is viewed as the ‘crown jewel’ of the RTA. The same can be said of Chapter 14 on ISDS which even has authority to review decisions by, for instance, a state court in the US. Further, we have also argued that free trade agreements between a hegemon and countries at a lower level of economic and political development may likely lead to the loss of ability by the party at the lower stages of development to adopt trade measures for the protection of its own industries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".