Water-Related International Investment Disputes: A Fresh Look at <i>Bayview Irrigation District v. United Mexican States</i>
Bibliographic record
Abstract
Water is one of the most vital resources on Earth. Furthermore, agricultural, industrial, environmental, recreational, and domestic uses of water all require fresh water in one form or another. Earth's exceedingly limited supply of fresh water, however, has led to countless water-related disputes. There are many theories on how best to combat water dispute problems; however, finding the complete solution has proven elusive up to this point. A front-runner, at least at the international level, is the idea of commoditizing fresh water as a good and subjecting it to international trade laws. However, the idea of regulating fresh water using international law raises many important questions. Of particular importance: To what degree should the North American Free Trade Agreement (NAFTA) apply to water disputes at the domestic and international level? The answer to this question has the potential to have far-reaching implications for water dispute issues in North America, as well as the rest of the world. Specifically, NAFTA's effect on fresh water flowing throughout Canada, the United States, and Mexico would create a significant impact on international investment disputes, as well as regulation of fresh water resources at all levels. The article addresses this increasingly important issue through a studied analysis of Bayview Irrigation District et al. v. United Mexican States.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".