Gouvernance des espaces publics urbains & planification stratégique : Enjeux substantiels et procéduraux. Cahier In.SITU 10
Bibliographic record
Abstract
Le projet Espaces publics (P.E.P) est une recherche réalisée en 3 volets par une équipe pluridisciplinaire de la Chaire internationale sur les usages et pratiques de la ville intelligente (ESG UQAM) pour le compte de la Ville de Montréal.En lien avec l’élaboration du Plan d’urbanisme et de mobilité (PUM) et du Projet de ville (2021) définissant les partis pris municipaux, les grands défis à relever et les éléments de vision pour guider la transformation de la ville d'ici 2050, la recherche contribue à « Définir une stratégie d’intervention pour la transformation des espaces publics de Montréal ». Ce Cahier In.SITU présente les résultats détaillés du volet 2. Il est consacré à une revue internationale des pratiques portant sur les enjeux substantiels et sur les caractéristiques de la gouvernance contemporaine relative à la prise en compte des espaces publics urbains dans la planification spatiale.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.002 |
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".