Le modèle coopératif, un atout à valoriser dans l’identité de marque employeur des coopératives financières ?
Bibliographic record
Abstract
S’appuyant sur le modèle Attraction/Sélection/Attrition (Schneider et al., 1995), cette recherche vise à explorer l’intérêt pour les coopératives financières de développer une marque employeur et d’identifier les bénéfices qui la composent (Ambler et Barrow, 1996) afin de mieux se distinguer des banques à capital-actions sur le marché de l’emploi. Des entrevues menées auprès de 21 responsables RH du Crédit Agricole (France) et de Desjardins (Québec) confirment qu’ils perçoivent que leur marque employeur se distingue de celle des banques actionnariales par des atouts symboliques, fonctionnels et économiques qui gagnent toutefois à être plus formalisés dans une identité de marque employeur claire et communiquée à l’interne comme à l’externe.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".