Québec est ses dilemmes urbanistiques : les enseignements du terrain et des débats médiatiques
Bibliographic record
Abstract
Les villes d’une certaine taille sont constamment interpellées par des enjeux ou projets urbanistiquesde différentes natures et dimensions. Québec vit actuellement une période de croissance, et plusieursdilemmes urbains se présentent simultanément dans la sphère publique et se télescopent, dans une certainemesure. Ces dilemmes se démarquent par la taille des projets et des investissements requis ainsi que par l’ampleur des effets pressentis. Les délibérations sur ces dilemmes sont intéressantes dans le sens où elles fontressortir différentes questions théoriques dans le champ de l’urbanisme. Nous traiterons donc de ces interrogations à l’aide d’une revue de presse sur les trois dilemmes identifiés, de quelques traitements statistiques et cartographiques ainsi que d’un retour sur les principes fondamentaux du champ de l’urbanisme qui sont mis à l’épreuve sur le terrain.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Not applicable | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".