Promoting Safe Use of Roads and Pathways for Active Transportation - A Review of Canadian Promising Practices
Bibliographic record
Abstract
Governments at all levels across the globe are promoting active transportation (AT - walking, bicycling) in pursuit of socially, environmentally and economically sustainable communities. However, with more concurrent use of the sustainable transport facilities by different user groups (e.g., children, youth, adults, seniors), there is concern over a counterproductive rise in the risk of conflicts and injuries. Along the same lines, many small, medium, and large Canadian municipalities are proactively promoting more active lifestyles and transportation to curb obesity, reducing greenhouse gases to reduce energy costs and mitigate climate change, and addressing the enormous economic costs of AT user injuries and deaths. With an intention to analyze and promote the safety of AT users (aka vulnerable road users - VRUs), this study was carried out on the safe use of roads and pathways for AT, sponsored by the Public Health Agency of Canada in 2012. This paper discusses the details and outcomes of this study focusing mainly on how community decision makers can best educate, engage and protect VRUs using informal, passive education tools. It had three main objectives. First was to conduct a comprehensive review of relevant sources to identify promising Canadian practices promoting safe use by VRUs. Second was to identify informal, passive AT safety education and enforcement programs. The final objective was to assimilate all collected data into a cohesive final report, which will be of interest to community decision-makers such as councilors, planners, engineers, public health practitioners, and other road safety stakeholders. This study employed an expedited, full-population sampling carried out in three parts. Firstly, primary information sources were identified via website scans of nearly 300 Canadian communities and literature review. Secondly, key informants were interviewed from a broad range of communities and organizations across Canada. Finally a national toolbox was assembled of promising informal, passive AT educational strategies, augmented by international literature for comparison. Many promising AT safety practices were identified by representatives of Canadian communities, but science based monitoring was not widely used. Future research should be conducted using observed critical success factors of the identified informal, passive AT safety education and enforcement programs to validate their significance and influence over program success. To increase effectiveness of the promising practices and realistic budgeting amounts, future research should address the identified lack of monitoring costs.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.017 | 0.031 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".