Socio-economic Evaluation of the Warrantage Mechanism in North Benin (West Africa): Case of the Maize and Rice Producers
Bibliographic record
Abstract
Warrantage is a type of proximity stock associated with a widely used credit system. It is a financing system that allows farmers to deposit their harvesting products in a warehouse managed by a farmer organization to receive a loan from a financial institution in return. The objective of this study is to carry out a socio-economic evaluation of the warrantage mechanism in northern Benin. Data were collected using questionnaires and interview guides from a sample of 94 rice and maize producers. The perception of the profitability of the warrantage transaction was analyzed using the Pearson chi-square homogeneity test, while the economic evaluation of this profitability was done using the profit margin calculation. The analysis of the strengths, weaknesses, potentialities and obstacles of the producer-level warrantage mechanism has been done through Kendall’s W-rank test. This study revealed that warrantage operation generated a high and positive profit margin for maize and rice crops. The study also revealed that the sale at a remunerative price, the good conservation of the stocks and the obtaining of credits constitute its strengths. The delay in setting up the credit granted and the unavailability of products for the treatment of stored products were weaknesses. The existence of micro-finance structures and the availability of producers to participate in the process have been the potentialities of the warrantage operation while the inexistence of market for the sale of stored products and the lack of adequate warehouses for storage constitute these obstacles. For a perfect success of this operation, it was hoped a more offensive awareness of beneficiaries and a timely start of the operation by the rapid introduction of credit to mobilize more producers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".