Gouvernance et planification collaborative
Bibliographic record
Abstract
Comment se prennent les décisions à l'échelle des régions métropolitaines et par qui sont-elles prises ? Quels sont les moyens utilisés par les parties pour arriver à établir et mettre en œuvre des politiques et des projets communs pour leur ville et leur agglomération ? Et quelle est la place de la participation publique dans ces décisions ? Bref, comment se déroulent les processus de planification à l'ère de la gouvernance et de la collaboration ? En mettant en parallèle cinq métropoles canadiennes – Québec, Montréal, Ottawa-Gatineau, Toronto et Vancouver –, cet ouvrage jette un regard neuf sur la construction de l'action publique territoriale et les régimes urbains. Issu des travaux conjoints de chercheurs canadiens en aménagement et en urbanisme, il illustre clairement les similitudes, les contrastes et les particularités des dynamiques de gouvernance et de planification de ces cinq régions. Il révèle finalement la nature des relations politiques qui lient les échelles d'action en matière d'aménagement et de développement, et analyse les rapports de force, les jeux de pouvoir et la nature des conflits qui en découlent.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".