Emergence de dispositifs de GRH partagés entre PME dans des clusters : enseignements à partir de six cas en France
Bibliographic record
Abstract
Cet article a pour objectif d’analyser l’émergence et la nature de dispositifs et de pratiques de gestion de ressources humaines (GRH) partagés par des PME, au sein de réseaux territoriaux d’organisations de type cluster. En mobilisant la méthode de l’étude multi-cas, l’analyse de six clusters en France a permis d’identifier des dispositifs de GRH partagés par des PME de trois natures (avortés, en projet, mis en oeuvre) et caractérisés par quatre types de pratiques de GRH (communication, formation, recrutement et gestion des compétences). L’analyse de ces dispositifs et de ces pratiques par l’approche des proximités souligne l’importance de la proximité géographique, associée à celles de la proximité socio-économique des ressources ainsi que de coordination, dans l’émergence des dispositifs de GRH dans les clusters. De plus, la place de la confiance liée à la direction du cluster est discutée.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".