Disciplining pedestrians: a critical analysis of traffic safety discourses
Bibliographic record
Abstract
This thesis examines how a non-profit organization, concerned with reducing injuries, promotes pedestrian safety in Canada. It is a case study which, from a critical perspective, uses several qualitative methods to locate the Canada Safety Council in its social context and to examine its conceptualizations of pedestrian safety within the ‘system’ of automobility. Through a review of relevant documents of the Canada Safety Council, this study examines safety promotion practices and discourses as they relate to the management of pedestrian risks. I discuss the political-economic implications of traffic safety promotion discourses within a neoliberal context that prefers individualized solutions to traffic risks. I argue that discourses of safety promotion discipline pedestrians and ultimately reinforce particular forms of mobility that support industries dependent on automobility. The promotion of pedestrian safety ensures pedestrians do not impede automobility and obscures a reconsideration of the adequacy of the ‘system’ of automobility for all people.
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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 | 0.024 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.040 | 0.053 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".