Revenu minimum d’insertion en France : les stratégies des acteurs
Bibliographic record
Abstract
L'instauration et la mise en oeuvre de la Loi sur le revenu minimum d'insertion a représenté en France un défi dans le champ du social. Il s'agit de combiner l'action sociale et les orientations économiques dans une prestation accordée aux plus pauvres. Ce revenu minimum est censé leur donner non seulement des moyens de survie matérielle mais aussi des possibilités d'insertion sociale. L'analyse de la loi dans son contexte d'apparition permettra de dégager la place faite au travail social dans ce dispositif. L'analyse des stratégies d'utilisation de la loi mises en oeuvre par les décideurs politiques, les bénéficiaires et les travailleurs sociaux donnera ensuite la possibilité de comprendre les articulations entre ces différents niveaux. Cette approche stratégique permettra finalement d'ouvrir des perspectives sur les pratiques sociales liées à la pauvreté et à l'exclusion.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".