Quantifying the United Nations’ Watercourse Convention Indicators to Inform Equitable Transboundary River Sharing: Application to the Nile River Basin
Why this work is in the frame
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Bibliographic record
Abstract
East African riparian countries have debated sharing Nile River water for centuries. To define a reasonable allocation of water to each country, the United Nations’ Watercourse Convention could be a key legal instrument. However, its applicability has been questioned given its overly generalized guidance and non-quantifiable factors. This study identified and evaluated appropriate indicators that best describe reasonable and equitable principles and factors detailed under Article 6 of the convention in order to allocate Nile River water among the states. Potential indicators (n = 75) were defined based on multiple sources that can address conflicting interests specific to this basin context. A questionnaire based on these indicators was developed and distributed to 215 prominent experts from five professional groups on five continents. To analyze the presence of agreements or disagreements within and outside of the basin, as well as differences across expert groups, a k-mean clustering analysis and statistical tests (ANOVA and t-test) were employed. The results imply agreement on 75% of the proposed indicators by all experts across all continents. However, a significant difference in identifying the importance and relevance of many indicators between experts from Egypt and other countries was evident. This study thus demonstrates how the UN watercourse convention principles can be quantified and applied to transboundary water allocation, and ideally lead to informed discourse between basin countries in conflict.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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