Legal and institutional adaptation to climate uncertainty: a study of international rivers
Bibliographic record
Abstract
This study seeks to understand why nations find it difficult to include climate-uncertainty mechanisms in treaties regulating international rivers. It also aims to examine the implications of not adopting these mechanisms, particularly during a crisis. The study focuses on the negotiation process of three water treaties, and seeks to identify the underlying reasons behind the inclusion - or exclusion - of such mechanisms. Second, it reviews how the treaties performed and evolved during drought. The first case study is the current drought along the lower Rio Grande and the 1944 water treaty between Mexico and the USA; the second is the 1961-1964 drought along the Great Lakes and the 1909 water treaty between Canada and the USA and, finally, it examines the 1997-2000 water shortage in the Jordan Basin and the 1994 treaty between Israel and Jordan. It was found that issues of sovereignty, water stress, power asymmetry, optimistic water scenarios and the nature of the treaties as “package deals” impede riparians from adopting some of these mechanisms. Among them is a joint institution with wide scope and geographical jurisdiction, an escape clause, allocating water according to percentage of flow, balance mechanism and a binding arbitration procedure. By excluding these mechanisms the anticipated political cost of an agreement decreases. However, this exclusion process limits the ability of these treaties and their institutions to manage a crisis situation, which may in turn engender controversy between the riparians as to how to divide the water in such a situation. Yet, it was found that during crises, treaties tend to evolve as the different parties supplement them with new legal and institutional measures that provide only partial immediate remedy to the crisis at hand. This stresses the need to incorporate mechanisms that are simultaneously politically feasible and hydrologically effective.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".