Farmers’ Participation Obstacles in Management of Irrigation Networks
Bibliographic record
Abstract
The purposes of this study are to analysis and group the participations’ obstacles of users in usage management and the irrigation networks maintenance in Semnan province. It was applied research and causal-correlation method was used. The statistical population of the study consists of all farmers having used irrigation networks in the Semnan province (Garmsar and Damghan town) having a population over of 18650 and finally 255 of which answered the questions. The main instrument used for date collection was questionnaire. To determine validity, the questionnaires were given to experts and some doctorate students, and then to evaluate reliability of the questionnaires, a pretest has been done, which was on 30 random farmers of Tehran (Varamin area), the gained questionnaire’s Alpha Coefficient was %88, it shows suitable reliability of the questionnaires. the main obstacles for the farmers’ participation were political obstacles (government’s inattention to roles of non–governmental organizations, the government’s inattention to users’ ownership right, the users being’s not clear of goals of participation, the focus of the maintenance and management activities of irrigation networks by the government, The government’s inattention to role of council) which have the most share (31.12) and then economical obstacles were (not economical in the maintenance and management of irrigation networks, lack of credits necessary for programs, usage management and the irrigation networks maintenance projects having the late outcome, financial inability for participation). Psychological and personal factors (unwell physical state for participation; programs are not adaptive with the farmers’ needs) which have the least share (3.39) in explaining total variance of the participations’ obstacles of users in usage management and the irrigation networks maintenance. These 5 factors explained 66.12 of total variance of all public participation’s obstacles in the usage management and the irrigation networks maintenance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".