Bibliographic record
Abstract
Abstract The international regulation of energy is complex, involving various legal frameworks such as economic agreements, environmental conventions, and dispute resolution mechanisms. These instruments often overlap and may not align, creating challenges for addressing energy-related issues. The United States–Mexico–Canada Agreement (USMCA) exemplifies these complexities. It addresses entitlements to natural resources, protection of energy-related transactions, cross-border energy policies, and environmental externalities. However, the USMCA does not fully resolve conflicts among differing policy goals within the energy sector. This article examines how the USMCA navigates issues related to resource entitlements, energy transactions, policy clashes, and environmental concerns. It argues that the absence of a unified energy policy leaves disputes to be balanced by resolution bodies, such as arbitration panels. The article scrutinizes each aspect of the USMCA’s approach and discusses potential mechanisms for resolving policy conflicts. The USMCA’s treatment of energy-related matters underscores the intricate interplay between international economic law and the energy sector, with implications for regional competitiveness and sustainability.
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 | 0.030 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.012 | 0.028 |
| Scholarly communication | 0.022 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".