Using ICT to Integrate Smallholder Farmers into Agricultural Value Chain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article examines an ICT-based intervention (known as the DrumNet project) that has succeeded in integrating smallholder-resource and poor farmers into a higher value agricultural chain. The article assesses the design of the project, and how it resolves the smallholder farmers’ idiosyncratic market failures and examines member-farmers’ marketing margins. The article finds that the design of the DrumNet project resolves smallholder farmers’ credit, insurance and information market failures and enables them to overcome organizational failure. The article concludes that successful ICT-based interventions for integrating farmers into higher value agricultural value chains require an integrated approach to tackling smallholder farmers’ constraints. The findings have implications for the design of future ICT-based interventions in agriculture.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it