Assessment of India's Agrometeorological Advisory Service from a farmer perspective
Bibliographic record
Abstract
This report summarizes the results of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) commissioned evaluation of India’s Integrated Agro-meteorological Advisory Service (AAS). Conducted June-July of 2012, this assessment was a joint endeavour of CCAFS, the International Crops Research Institute for the Semi-Arid Tropics, and the India Meteorological Department (IMD). The assessment sought to offer transferable lessons that can guide investment in climate/agro-meteorological advisory services elsewhere in the world. Researchers conducted focus groups and individual interviews with 132 male and female farmers in eighteen villages across six states about how they receive and use AAS advisories, perceived gaps, and suggestions for improvement. The assessment uncovered the key role of diverse communications approaches. In villages where many communications channels were used to disseminate AAS information, such as SMS and voice messaging, meetings and trainings with agricultural extension officers, local knowledge centers, farmers clubs, and announcements over the microphone in villages, awareness and use of AAS advisories was higher. Farmers noted that trainings and discussions with agricultural extension officers at the village level were their preferred form of receiving information. However, ensuring wide representation in discussions is critical. In villages where women were fully engaged in receiving and disseminating AAS information, use and potential benefit from the program were maximized. Women overall had lower awareness of AAS than men do, indicating the importance of targeting women and information that responds to the demands of women in communications efforts. The establishment of specific trainings and discussions on AAS for women farmers in the villages was recommended by farmers, as were trainings and interactions with scientists that all farmers can attend. Membership in women’s or farmers groups may be a positive factor in increasing awareness of AAS information, and extension services targeting existing local groups could be a strategy for increasing the impact of AAS information.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".