Adaptation to Climate Change and Technical Efficiency in Paddy Farming: A Case Study in Wayanad and Palakkad Districts, Kerala
Bibliographic record
Abstract
The Intergovernmental Panel on Climate Change has consistently recognized the anthropogenic nature of climate change and its impact on global systems, particularly agriculture.Recognizing the vulnerability of the agricultural sector, organizations like the Food and Agriculture Organization and the United Nations Framework Convention on Climate Change have emphasized the urgent need for sustainable agricultural practices to mitigate the adverse effects of climate change.This study investigates the link between farmers' adaptive capacity, technical efficiency, and overall agricultural sustainability.Using stochastic frontier analysis, the research examines data from 330 paddy farmers in Wayanad and Palakkad, two climate-vulnerable districts in Kerala, India.The findings reveal a strong positive correlation between climate adaptation practices, coping strategies, and the technical efficiency of paddy farming.However, the study also highlights that a lack of comprehensive coping strategies can hinder farmers' ability to effectively address climate change impacts.This underscores the crucial need to integrate both climate adaptation practices and coping strategies into farmlevel planning to enhance the long-term sustainability of agriculture in the face of a changing climate
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".