Les contrats de ville en Hauts-de-France : bilan et perspectives
Bibliographic record
Abstract
The Hauts-de-France region has the largest number of city contracts, priority neighborhoods, municipalities and inter-municipalities; making it highly involved in urban policy. A plethora of measures, schemes and programmes are implemented each year to meet the challenges of this cross-cutting policy, in particular with the support of structures such as the resources centers. Nonetheless, the final evaluation of the 2015-2023 city contracts revealed that certain issues (such as citizen participation and the fight against discrimination) were not being led effectively at local level, demonstrating at the same time a proactive policy that is continually ambivalent. This year, the urban policy programme was turned upside down by the urban riots that followed the death of a young resident of a priority neighbourhood (on 27 June), plunging the pilots of the city contracts into a horde of concerns and questions. The drafting of future city contracts, due to start in the first quarter of 2024 and run until 2030, has therefore found itself competing with the security issue at the heart of the debates, fuelling fears that the social side of urban policy will "give way" to law and order initiatives.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| 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".