La succession dans les entreprises familiales dirigées par les femmes : une problématique en quête de chercheurs
Bibliographic record
Abstract
La succession est l’un des volets ayant le plus été étudié en contexte d’entreprises familiales. Pourtant, bien que l’on évalue à plus de 33 % la part des entreprises appartenant à des femmes, à notre connaissance, aucune étude ne s’est encore intéressée à la problématique dans leur cas. En conséquence, l’objectif de cet article est d’expliquer comment deux champs de recherche jusqu’ici séparés peuvent être complémentaires dans la manière d’aborder la problématique de la succession en général. Il s’agit donc d’un exercice de réflexion qui, somme toute, soulève un débat d’actualité sur l’état de nos connaissances sur les femmes entrepreneures en contexte d’entreprises familiales et qui se verront bientôt confrontées à une problématique de taille, celle de la succession.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".