Allocating water resources in transboundary river basins: A sequential rubinstein bargaining approach with risk discounting
Why this work is in the frame
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Bibliographic record
Abstract
Study region The Mekong River Basin Study focus This study reduces the multi-agent bargaining game to a one-to-one model by assuming downstream countries act as coalitions in water allocation scenarios. Each country’s risk level and perception inform its discount factor, which is then aggregated and converted into coalition discount factors through weighted averaging. Then, a Rubinstein bargaining water allocation model with multi-agent participation and multi-stage negotiation is constructed and applied to allocate water in the Mekong River Basin. New hydrological insights for the region The proposed Multi-stage Rubinstein Bargaining Model produced allocations that were more stable than those generated by traditional bankruptcy rules such as Proportion, Adjusted Proportion, Constrained Equal Loss, Constrained Equal Award, and Shapley. Therefore, this allocation framework can serve as both a theoretical foundation and a practical tool for water allocation in transboundary river basins.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it