Modes d’articulation entre travail, recherche et formation. Entre meilleures pratiques et pratiques réflexives, peut-on orienter la formation vers le développement d’un métier ?
Bibliographic record
Abstract
Cet article s’intéresse à la question de l’articulation entre pratiques professionnelles, recherche et formation dans le champ de l’intervention sociale. Dans un premier temps, nous discutons trois modèles d’articulation de ces champs : le modèle des meilleures pratiques, celui des pratiques réflexives et celui du développement du métier. Dans un second temps, les rapports pratique/recherche/formation proposés par la perspective du développement du métier seront développés et illustrés par une recherche explorant les sens donnés au travail par des intervenant-e-s sociaux, et par un enseignement qui a été alimenté par les observations et analyses issues de cette recherche.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.055 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.010 | 0.086 |
| Scholarly communication | 0.028 | 0.029 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".