From the drawing board straight to the archives: Exploring the pattern of unimplemented small town planning documents through the case of St. Stephen, New Brunswick
Bibliographic record
Abstract
Trop souvent, des plans d’urbanisme, préparés pour des villes de petite taille, sont tablettés et en effet destinés à ramasser de la poussière. Maintes fois, ces plans ne sont pas instaurés, en raison d’un manque de ressources – financière, technique et administrative entre autres. Mais pourquoi est-ce que ces plans, peu réaliste ou inachevable, sont préparés du tout ? La plupart des plans d’urbanisme pour des villes de petite taille, sont faite par de consultants provenant de plus grands centres. Ces consultants ne sont pas nécessairement familiers avec les divers contextes locaux, ni avec les réalités confrontant des villages et milieux ruraux. À travers une exploration de la littérature, touchant les défis urbanistiques propres aux petites villes, ce projet présente un cadre théorique pour la préparation de plans d’urbanisme qui peuvent être ambitieux, mais, qui sont également en mesure d’être mis en oeuvre?
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.031 | 0.018 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".