Economic Analysis of the Role of Farmer Organizations in Enhancing Smallholder Potato Farmers’ Income in Middle Guinea
Bibliographic record
Abstract
Farmers’ organizations are inclusive of the poor and are charged with the purpose of becoming a market outlet for smallholder farmers in Guinea. Improving farmers’ income earning capability and agricultural productivity has been an important strategy of Guinea’s agriculture development policy. However, despite their growing importance, empirical studies on how farmers’ organizations have impacted their members’ income are limited in Guinea. This paper investigates the determinants and effects on farm income of group membership, using the sample of 90 smallholder potato producers in Middle Guinea. A probit model was used as a selection equation to identify factors that influence group membership decision by smallholder potato farmers. The results revealed that the age of the potato farmers, land ownership, extension service, credit access and off-farm income are positively associated with group membership while gender and education level of the farmer negatively influenced their decision to join farmer groups. Results of the second stage outcome equation found positive farm income effects of group membership. Furthermore, results revealed that farm income is predominantly determined by labor used, the size of the cultivated potato area, share of potato sold and potato market price. Since farmers are resource-poor and that farmer organizations are constrained by various institutional, technical and investment constraints despite their potential, it is recommended that favorable polices should be geared toward smallholder agriculture in Guinea in order to ensure the success of farmer organizations. Our results show that farmer groups can be an important institution for the transformation of smallholder farming, increase productivity and incomes thereby reducing poverty. Agricultural policies in Guinea should therefore focus more on the intensification of agriculture and farmers’ organizations and increase the market orientation of the smallholder farm sector.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".