A Novel NGO Approach to Facilitate the Adoption of Sustainable Innovations in Low-Income Countries: Lessons from Small-scale Farms in Nicaragua
Why this work is in the frame
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Bibliographic record
Abstract
There are about 500 million small-scale farms in low-income countries on the planet. Farmers have been slow to adopt a threefold set of sustainable agronomic practices known as “conservation agriculture” (CA) that have been shown to double productivity. Our study of a novel CA project in Nicaragua, organized based on principles that counter convention, may point to improved ways of understanding and managing sustainable innovations in low-income countries. In particular, by connecting core ideas from the innovation literature to the literature that explores the role of intermediaries such as NGOs, our case study suggests that the efficacy of NGOs to facilitate the adoption of sustainable innovations by small-scale farmers in these settings may be enhanced if NGOs employ non-centrist approaches in order to address the critical uncertainties associated with such innovations. We discuss how our findings contradict some of long-standing arguments in the literature, and their implications for theory and practice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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 it