Living Labs et territorialisation de politiques publiques innovantes. L’exemple du Living Lab Jeunesse de la Métropole de Lille (France)
Bibliographic record
Abstract
Les Living Labs peuvent être initiés par la société civile pour pallier les manques de l’État-providence, mais cet outil est de plus en plus mobilisé par la puissance publique pour associer des usagers à la transformation des politiques publiques. L’article propose trois types de Living Labs et trois scénarios d’usage pour innover dans l’action publique, selon l’engagement des citoyens, des parties prenantes et des décideurs publics. Ce modèle est testé sur le cas du « Living Lab Jeunesse » de la Métropole de Lille (France), expérimentation financée sur appel à projets national pour co-construire avec les jeunes une politique sociale innovante à l’échelle d’un territoire métropolitain. Cette étude de cas montre comment les institutions publiques peuvent articuler les trois types de Living Lab sur le temps long pour transformer l’action publique étape par étape.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".