Réduire les usages de l’automobile en ville : une comparaison des débats médiatiques sur la réduction de la vitesse à 30 km/h à Paris et à Montréal
Bibliographic record
Abstract
Cet article propose une analyse des débats médiatiques sur la limitation de vitesse à 30 km/h à Paris et à Montréal, comme mesure visant à réduire la place de la voiture en ville. Pour comprendre le contenu des discours et les représentations véhiculées par les différents acteurs, l’article s’appuie sur une analyse de la presse à partir d’un corpus de 184 articles publiés entre 2013 et 2018. Les résultats montrent que plus les objectifs de réduction de la place de la voiture sont forts, plus la presse traite le sujet des 30 km/h de manière continue, approfondie et nuancée. Plus le système automobile est mature, plus la presse mobilise des arguments répondant à l’ensemble des nuisances de l’automobile. La presse traduit et véhicule un changement de mentalité face à l’automobile.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".