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Record W2037273844 · doi:10.3917/edd.261.0005

Les tontines favorisent-elles la performance des entreprises au Cameroun ?

2012· article· fr· W2037273844 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevue d économie du développement · 2012
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.057
GPT teacher head0.247
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it