Implementing participatory irrigation management in Thailand
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
Participatory Irrigation Management (PIM) was formally adopted in Thailand in 2004. The involvement of farmers in water management decision making is necessary to meet the implementation challenges of this initiative. As such, the research presented in this paper considered the level of farmer involvement in water management and decision making, and the lessons learned by both government officials and farmers through the implementation of PIM in Thailand to date. Data collected from document reviews and a total of 44 semistructured face-to-face and telephone interviews of public irrigation officials and farmers nationwide show that farmers possess the full potential to manage irrigation water by themselves, and that they are making important changes to governance systems for irrigation. However, they need both the opportunity and the continuing supportof public irrigation officials for success, which is currently only being partly achieved through the PIM initiative.
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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 | 0.000 |
| 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