Adopting a Safe Systems Approach to Road Safety: Using the Consolidated Framework for Implementa- tion Research to Examine Injury Prevention and Transportation Professionals’ Perceptions of Vision Zero in Five Canadian Municipalities
Bibliographic record
Abstract
Aims The aim of this research is to highlight the perceptions and experiences of injury prevention and transportation professionals regarding Vision Zero and how the adoption of this strategy influences their work. Our results are useful to road safety researchers and practitioners who are interested in barriers and facilitators to implementing Vision Zero in the Canadian context. Background Road traffic collisions are a leading cause of injury in Canada. Vision Zero is a Safe Systems Approach (SSA) that accommodates human vulnerability and error, with the goal of zero deaths and injuries. Objective This paper enhances knowledge of Vision Zero in Canada and examines key barriers and facilitators using the Consolidated Framework for Implementation Research (CFIR). Methods Qualitative data were collected from injury prevention and transportation professionals in five municipalities: Vancouver, Calgary, Peel Region, Toronto, and Montréal. Interviews and virtual focus groups gathered data from participants across sectors: policy/decision-making, transportation, public health, non-profit, university researcher, community associations, and private. Thematic analysis was used to analyze the data. Results Data mapped onto six CFIR constructs across three domains: 1) Innovation, 2) Outer Setting, and 3) Implementation Process. Innovation Complexity, Local Attitudes, Local Conditions, and Assessing Context were identified as barriers and facilitators. Innovation Evidence Base and Partnerships and Connections were identified solely as facilitators. Conclusion Vision Zero implementation is complex and requires evidence. Local Attitudes and Local Conditions highlight the importance of partnerships for Vision Zero to be accepted and understood. Further, Vision Zero is a facilitator for road safety work. The CFIR domains and constructs elevate our understanding of how Vision Zero is implemented. Results are useful to municipalities interested in adopting and implementing Vision Zero in Canada.
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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 | 0.086 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.017 | 0.019 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| 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".