Bibliographic record
Abstract
En France, les municipalités disposent d’une marge de manœuvre importante en matière de régulation de l’islam. Le cas de la grande mosquée de Créteil est à ce titre intrigant. Non seulement elle se distingue par la rapidité de sa réalisation, mais elle se démarque aussi par sa centralité et sa visibilité. En plus de la volonté politique du maire, une des explications souvent mises de l’avant par les acteurs locaux est le processus de concertation. Qu’en est-il exactement ? Pourquoi la municipalité a-t-elle choisi cette stratégie de publicisation de l’enjeu et quels en sont les effets sur l’action publique ? En considérant la concertation comme un instrument, l’article se penche sur trois effets que l’on peut lui attribuer. Sans disqualifier les effets en matière de démocratisation et d’instrumentalisation, nous verrons que la consultation médiatise et hiérarchise des représentations spécifiques de l’islam. Elle révèle des formes particulières de régulation politique de l’islam, soit sa municipalisation.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".