Diversité des pratiques tutorales des artisans maîtres d’apprentissage : le cas du recrutement et de la formation des apprentis de niveau V
Bibliographic record
Abstract
Cette contribution vise d’une part à étudier les motifs pour lesquels les maîtres d’apprentissage (MA) artisans recrutent des apprentis et d’autre part à repérer la diversité des pratiques tutorales qu’ils mettent en œuvre en matière de sélection et de formation. L’étude empirique menée auprès de 285 MA montre que si un des objectifs du recrutement est pour eux de former une main-d’œuvre qualifiée, il répond aussi à des motifs de transmission du métier aux jeunes générations. Les résultats confirment que les entreprises présentent des formes diversifiées de pratiques tutorales dans des conditions d’accueil et de modes différents de socialisation.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".