Cars before Kids: Automobility and the Illusion of School Traffic Safety
Bibliographic record
Abstract
La sécurité routière constitue une question d'intérêt public très discutée, et ses pratiques fortement débattues exigent une analyse sociologique et l'attention systématique des politiques publiques. Dans cette étude, les auteurs analysent les programmes de sécurité routière dans les écoles primaires de Vancouver, en Colombie‐Britannique. Ils illustrent comment de tels programmes supposent une politique de la responsabilité visant grandement les enfants et les parents pour en faire des personnes sécuritaires sur la route dans un environnement institutionnel qui ne fournit pourtant aux programmes qu'un soutien et des fonds sporadiques pour administrer les risques de la circulation. Alors que ce contexte de programmes de sécurité routière à l'école aide à maintenir une certaine « illusion de sécurité», elle ne remet pas fondamentalement en question la structure dominante actuelle de la mobilité et les problèmes qui y sont inhérents. Traffic safety is a contested public issue and highly negotiated practice that requires sociological analysis and systematic public policy attention. In our case study, we examine elementary school traffic safety programs in Vancouver, British Columbia. We illustrate how such programs assume a politics of responsibility that largely targets children and parents for traffic safekeeping within an institutional environment that gives programs only sporadic support and funding to manage traffic risks. While this context of school traffic safety programs helps to maintain an “illusion of safety,” it does not challenge the current auto‐dominant mobility structure and its inherent problems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".