Pertinence du tutorat comme dispositif d’accompagnement du repreneur individuel après la reprise. Une étude empirique à l’échelle européenne
Bibliographic record
Abstract
Si l’accompagnement entrepreneurial est un champ de recherche en croissance, il existe encore peu de travaux sur l’accompagnement « repreneurial ». Cet article s’intéresse donc à la spécificité des besoins des repreneurs en matière d’accompagnement post-reprise et aux formes que cet accompagnement peut prendre. S’appuyant sur un projet test réalisé à l’échelle européenne sur un échantillon de 889 reprises, les auteurs confirment empiriquement la pertinence du tutorat comme forme particulière d’accompagnement dans cette phase délicate. Ils montrent ensuite dans quels types de situation et pour quels types de repreneur un tutorat s’avère le plus bénéfique.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".