Les tontines favorisent-elles la performance des entreprises au Cameroun ?
Bibliographic record
Abstract
Résumé Les Associations d’épargne et de crédit rotatif (AECR), connues aussi sous le nom de tontines au Cameroun et en Afrique francophone, constituent l’une des formes d’organisation les plus populaires pour financer des projets dans les pays où l’accès au crédit est restreint. Dans cette étude, nous analysons l’effet de la participation aux tontines entrepreneuriales sur la performance des entreprises. À l’aide de données du secteur manufacturier, nous examinons, en particulier, l’hypothèse selon laquelle les réseaux sociaux auxquels les tontines sont associées permettent d’avoir accès à des fonds financiers, de surmonter les défaillances du marché formel ainsi que d’améliorer la performance entrepreneuriale. Nous observons que les tontines ont un effet positif et significatif sur la croissance de l’emploi et des ventes au sein des entreprises. De plus, les résultats étayent l’hypothèse selon laquelle les ressources tontinières servent principalement à financer les flux de trésorerie plutôt qu’à augmenter le capital ou qu’à réaliser des investissements. Classification JEL : 012, O17, G21
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".