Comment concilier auto-organisation et contrôle au sein des communautés de pratique pilotées ? : une scoping review
Bibliographic record
Abstract
L’objet de cette contribution est de déterminer, à travers une scoping review, dans quelle mesure la nécessaire conciliation entre auto-organisation et contrôle que nécessitent les communautés de pratiques pilotées implique de concevoir une nouvelle façon de piloter l’action collective et de déterminer les éléments caractéristiques de cette nouvelle forme de pilotage notamment en termes de gouvernance et de profils de manager. A travers une typologie, nous abordons ces éléments de manière différenciée entre communautés stratégiques d’exploration et communautés opérationnelles d’exploitation. Le pilotage des premières nécessite, selon nous, de faire appel à un manager au profil d’intrapreneur, capable de gérer une tension contrôle/auto-organisation particulièrement exacerbée. Les secondes nécessitent de s’appuyer sur un expert bénéficiant d’une forte légitimité cognitive et sociale.
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 | 0.050 | 0.208 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".