Evaluating the Effectiveness of Picture-Based Agricultural Extension Lessons Developed Using Participatory Testing and Editing with Smallholder Women Farmers in Nepal
Bibliographic record
Abstract
Printed pictures are traditional forms of agricultural extension for smallholder farmers. They receive historical academic criticism but remain inexpensive, do not require technical skills (unlike smartphones), and bypass language/literacy barriers. Here, a comprehensive participatory pipeline is described that included 56 Nepalese women farmer editors to develop 100 picture-based lessons. Thereafter, the Theory of Planned Behavior is used as a framework to evaluate 20 diverse lessons using quantitative and qualitative data (Nvivo-11) collected from four groups, focusing on low-literacy women: the women farmer editors (n = 56); smallholder field testers who had prior exposure to extension agents and the actual innovations (control group, n = 120), and those who did not (test group, n = 60); expert stakeholders (extension agents/scientists, n = 25). The expected comprehension difference between farmer groups was non-substantive, suggesting that the participatory editing/testing approaches were effective. There were surprising findings compared to the academic literature: smallholders comprehended the pictures without the help of extension agents, perhaps because of the participatory approaches used; children assisted their mothers to understand caption-based lessons; the farmers preferred printed pictures compared to advanced information and communication technologies (ICTs); and the resource-poor farmers were willing to pay for the printed materials, sufficient to make them cost-neutral/scalable. These findings have implications for smallholder farmers beyond Nepal.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".