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Innovative behaviour of awardee farmers in Konkan region

2025· article· en· W4414816362 on OpenAlexaboutno aff
SS Devrukhkar, HV Borate, AS Shigwan, MH Khanvilkar, Ankur R. Desai, RB Kayande

Bibliographic record

VenueInternational Journal of Agriculture Extension and Social Development · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureSample (material)Quarter (Canadian coin)De factoData collection

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.147

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.281
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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