Bibliographic record
Abstract
This concluding chapter discusses trade disputes and other matters which while not directly related to USMCA could affect the ultimate success of the USMCA in achieving the goals of the parties and stakeholders. These include US Section 232 tariffs on steel and aluminum (and those threatened on autos and auto parts), with the first two applied to most of the countries that export steel to the United States, whether rivals or allies. (Canada and Mexico were excluded in May 2018 as a condition of approving the USMCA.) Similarly, the ongoing China-United States trade war, despite the truce reflected in the January 2020 agreement, is likely to have an impact on the North American economies for years to come. High US tariffs on Chinese goods could encourage some enterprises to move their operations from China to Mexico, but the tariffs will make production costs for many North American enterprises higher than those of their competitors in China and Asia. China’s retaliatory tariffs will discourage some US exports to China. Indirectly, the demise of the WTO dispute settlement system will have potentially significant impacts on the rules-based international trading system. Finally, the unpredictability of the policies that may be implemented by Presidents Trump and L—pez Obrador promise uncertainties for stakeholders throughout North America.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".