Identifying and Overcoming Barriers to the Implementation of Active Transportation
Bibliographic record
Abstract
This research paper investigates the implementation of Ontario’s provincial and municipal policies that seek to build communities that encourage walking and cycling. Although policies have recently come a long way in recognizing and promoting active transportation, aligning policy is different than aligning practice, and current policies are not necessarily translating into successful on-the-ground implementation. This paper explores the institutional barriers that exist in detailed planning, development, engineering, and construction process that have not caught up with higher-level policies including engineering standards and other institutionalized practices. Research objectives included charting real-world decision-making processes that move “policy” to “implementation” when it comes to infrastructure that prioritizes active transportation, identifying policy gaps and/or the need for new or updated tools (such as professional guidelines/standards, education/training, regulatory updates, etc.) to facilitate the achievement of active transportation policies. In order to better understand how provincial policies are or are not translating into current practices, between 2013 and 2014 the research team: (1) conducted a review of provincial policy, municipal policy, and professional street design guidelines such as those produced by the Transportation Association of Canada (TAC); (2) conducted two focus group sessions with planning and engineering professionals; (3) and carried out several case studies of Toronto area road projects that either incorporated, or failed to incorporate, active transportation facilities. The research was also carried out with the assistance of an advisory group of professionals involved in AT planning and design that reviewed project reports and provided critical feedback and insight into the policies and processes involved in providing active transportation facilities. Overall, the research found that despite high level policies that encourage active transportation, institutionalized barriers continue to exist that promote roadway design primarily oriented toward accommodating motor vehicles. In some cases, such as the Municipal Class Environment Assessment, there is not consensus on how the process does and does not create barriers to active transportaiton, nor how the process should work. The promotion of motor vehicle roadway design in other cases, such as the standardized and often mandated performance measures such as Level of Service and Traffic Impact Studies, was much clearer. Complex interactions between different levels of government, the ways that the capital budgeting process works, and other aspects of how roadways are financed, designed, and produced all interact to produce environments that continue to prioritize the accommodation of motor vehicles, sometimes despite policy.
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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 | 0.026 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".