Are shared benefits of international waters an equitable apportionment
Bibliographic record
Abstract
This brief article examines the case for applying a shared benefits strategy to the development of an international river basin as a substitute for the more traditional method of allocating a basin's water supply among riparian nations bordering an international river. The article traces the origin of the theory, articulates several objections, and examines two case studies of shared benefits. The concept of benefits sharing with respect to water is said to have originated in the negotiations over the Canada-United States Columbia River Treaty. We find that there are lingering doubts in Canada about the success of the treaty in allocating benefits to both parties; Canada's use of the Columbia continues to be primarily hydropower production for the United States. The second case study considers the Amu and Syr Darya basins in Central Asia. Benefit sharing has been adopted as the theory for basin development, but unrestrained unilateral action, unsustainable agricultural practices, and corresponding ecosystem degradation continue. Four possible problems with the substitution of benefit sharing for traditional allocation are identified and discussed, including buyer's remorse, the sacrifice of aquatic ecosystems for monetary gain, the construction of new dams of dubious benefit, and the failure to address the problems of adaptation to global climate.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".