L' aménagement et l’urbanisme à l’épreuve de la COVID-19 : les perceptions des professionnels œuvrant en MRC au Québec
Bibliographic record
Abstract
En mars 2020, le Québec était frappé de plein fouet par la pandémie de COVID-19. Cette catastrophe, qui allait durer plus de trois ans, a eu des effets multiples, notamment dans le champ de l’aménagement et de l’urbanisme. L’objectif général de cet article est de connaître les perceptions et les réactions des intervenants œuvrant au sein des Municipalités régionales de comté (MRC) au cours de la pandémie de COVID-19. Au-delà du sentiment généralisé d’un regain d’intérêt envers les milieux ruraux et la villégiature, plusieurs effets négatifs ont été notés : crise du logement, mobilité réduite, fragilisation du tissu commercial, etc. Ces impacts ont été perçus comme importants, peu importe la localisation des MRC. En dépit de cela, la plupart des professionnels œuvrant en MRC ayant participé à l’étude semblent considérer que les documents de planification en vigueur répondaient aux dimensions territoriales de la catastrophe sanitaire.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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, 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".