Différenciation et dualisation de l’action publique : le cas des quartiers fragiles et de la jeunesse urbaine en France
Bibliographic record
Abstract
En France, les services publics recevant de jeunes urbains, comme les politiques en direction de la jeunesse, sont particulièrement concernés par les mises en tension des services publics (public-privé, égalité-mixité, etc.) et par les contradictions territoriales, sectorielles et techniques de l’action publique urbaine. Qu’il s’agisse de culture, d’éducation, de sport ou de prévention de la délinquance, les politiques ciblant les jeunes visent à réduire ces contradictions en s’accommodant des tensions évoquées, voire en les dépassant par l’innovation administrative et la proximité. Il en est ainsi de l’adaptation du service public à l’usager, des actions ciblées spatialement, des dispositifs transversaux et partenariaux. Mais ces politiques sont elles-mêmes duales, entre d’un côté les filières traditionnelles plus ou moins reconfigurées (Contrat éducatif local, Contrat temps libre jeunesse, etc.) et, de l’autre, les actions et équipements spécifiques des « nouvelles politiques sociales », dont la répartition se limite à certains territoires ou publics particuliers. On retrouve ces fameuses tensions, non entièrement résolues.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".