A scoping review of the contributions of farmers’ organizations to smallholder agriculture
Bibliographic record
Abstract
Farmers' organizations (FOs), such as associations, cooperatives, self-help and women's groups, are common in developing countries and provide services that are widely viewed as contributing to income and productivity for small-scale producers. Here, we conducted a scoping review of the literature on FO services and their impacts on small-scale producers in sub-Saharan Africa and India. Most reviewed studies (57%) reported positive FO impacts on farmer income, but much fewer reported positive impacts on crop yield (19%) and production quality (20%). Environmental benefits, such as resilience-building and improved water quality and quantity were documented in 24% of the studies. Our analysis indicates that having access to markets through information, infrastructure, and logistical support at the centre of FO design could help integrate FOs into policy. Natural resource management should also be more widely incorporated in the services provided by FOs to mitigate risks associated with environmental degradation and climate change. Finally, farmers who are already marginalized because of poor education, land access, social status and market accessibility may require additional support systems to improve their capacities, skills and resources before they are able to benefit from FO membership.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".