Impact of Unequal Distribution of Canal Water on Farm Produce: A Case Study Matli Taluka
Bibliographic record
Abstract
This study seeks to investigate to identify the impact of shortage of water on the tail, end areas of the irrigation network. For the research study 320 respondents were randomly selected and nearly 107 from each category that is large medium and small farmer’s respondent. The sample further stratified respondents from all three reaches that is head middle and tail of main semi-irrigation channels and on the water courses level as well to capture the authentic picture of the water availability on each level of irrigation system. The observation of the study and data collected revealed that farmers on the head reaches benefit more from the supply of water from crop production compare to middle and tail reaches and middle reaches have more opportunity of having better irrigation water compare to the tail reaches however, the more sufferers are the tail reach farmers who get less water from crop production. Consequently, this situation cause’s absolute poverty to the farmers on the tail reaches of the irrigation water supply channels.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".