Water When It Counts: Reducing Scarcity through Irrigation Monitoring in Central Mozambique
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
Management of common-pool resources in the absence of individual pricing can lead to suboptimal allocation. In the context of irrigation schemes, this can create water scarcity even when there is sufficient water to meet the total requirements. High-frequency data from three irrigation schemes in Mozambique reveal patterns consistent with inefficiency in allocations. A randomized control trial compares two feedback tools: i) general information, charting the water requirements for common crops, and ii) individualized information, comparing water requirements with each farmer's water use in the same season of the previous year. Both types of feedback tools lead to higher reported and observed sufficiency of water relative to recommendations, and nearly eliminate reports of conflicts over water. The experiment fails to detect an additional effect of individualized comparative feedback relative to a general information treatment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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