Modèle de revenus et flux de valeur : vers un modèle de performance inversé de l’entreprise sociale
Bibliographic record
Abstract
En dépit de l’intérêt porté à l’entrepreneuriat social par la communauté académique, la singularité de son modèle de revenus (MR) reste peu étudiée. Dans cet article, nous mobilisons la littérature sur la création de la valeur pour examiner le MR à la lumière des flux de valeur qui le relient au modèle d’affaires (MA), dont il est la composante financière. À l’aide d’une méthodologie qualitative immersive, les liens entre MR et MA ont été mis au jour. Les résultats montrent la nécessité de réfléchir le MR en relation avec les propositions de valeur émises à l’endroit de différentes cibles. Ils soulignent l’importance d’une expérimentation sociale, source de performance financière, et indiquent l’utilité de liens partenariaux forts et diversifiés, fondés sur un modèle de performance inversé.
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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 | 0.004 | 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 | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".