Caisse d’épargne et ADIE : une confirmation partenariale innovatrice
Bibliographic record
Abstract
Alors que les forces du marché poussent les organismes de crédit coopératif vers la banalisation, on observe aussi des forces de réciprocité qui font émerger des partenariats entre ces organismes et des associations dans le champ du micro-crédit solidaire. Une configuration partenariale est étudiée dans cet article : la Caisse d’épargne Île-de-France-Paris (CE IDF-Paris) et l’Association pour le droit à l’initiative économique (ADIE) Île-de-France, partenaires dans l’offre de prêts à des micro-entrepreneurs. L’approche socio-économique permet de dégager les caractéristiques institutionnelles et organisationnelles de ce partenariat, de même que les perspectives ouvertes. Ainsi, si ce partenariat permet de mieux répondre aux besoins de personnes exclues du marché financier, il contribue ce faisant à l’actualisation du projet fondateur de la caisse.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".