A critical review of the Ganges Water Sharing arrangement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The 1996 Ganges Water Sharing Treaty was an important breakthrough in solving disputes over sharing Ganges water between India and Bangladesh. This study evaluates cooperation reflected in the Treaty by performing a quantitative analysis on available water sharing data. The study recognized that inaccurate projection of future flow and the obligation of allocating guaranteed 991 m3/s flows perpetuate the ongoing water sharing conflicts. The provision of guaranteed minimal flow alternately to India and Bangladesh during critical periods leads to frequent occurrences of low-flow events. Results indicated that the Treaty underestimated the impact of climate variability and possibly increasing upstream water abstraction. Statistical analysis of the post-Treaty data (1997–2016) also indicated that 65% of the time Bangladesh did not receive its guaranteed share during critical dry periods with high water demand. It is advised to project the reliable water availability using a combination of modelling and improved observation of river flows. In addition, the condition of minimum guaranteed share should be removed to reduce the frequency of low-flow events in future. Although our analyses show a number of weaknesses, the Treaty could still enhance the future regional cooperation if some adjustments are made to the current terms and conditions.
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.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it