Innovative behaviour of awardee farmers in Konkan region
Bibliographic record
Abstract
The present study examines the innovative behaviour of awardee farmers in the Konkan region of Maharashtra, recognising their role as potential change agents in agricultural development. The research was conducted across five districts viz., Thane, Palghar, Raigad, Ratnagiri and Sindhudurg and involved a sample of 40 farmers who had received state-level agricultural awards between 2012 and 2023. Respondents were selected through proportionate random sampling, and data were collected using a pre-tested interview schedule. An ex-post facto research design was employed to assess their innovative behaviour. The findings revealed that three-fourths of the respondents (75.00 per cent) fell within the medium to very high categories of innovative behaviour, while a quarter exhibited low or very low levels. This variation underscores both the achievements and the untapped potential of award-winning farmers in the region. The study highlights the need for targeted capacity-building programmes, farmer-to-farmer learning, and policy support to enhance the innovative behaviour of these farmers and promote wider diffusion of best practices.
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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 | 0.002 |
| 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) | 0.002 | 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".