Assessing the potential of cycling growth in Toronto, Canada
Bibliographic record
Abstract
Cycling is seen as a desirable modal choice due to the environmental, economic and social benefits to individuals and cities. While North American cities have expanded their targeted infrastructure and programs, cycling still is a marginal mode compared to modal shares observed in western Europe. In an effort to promote a more sustainable transport future, the City of Toronto has highlighted two key policy objectives in the City’s Official Plan for 2050: (i) to ensure that all residents are within one kilometer of a designated cycling route, and (ii) 75% of trips under 5 km are walked or cycled. This paper evaluates the potential for cycling in Toronto considering different cycling vehicles, areas, trip purposes and demographics, and how these change given the presence of cycling infrastructure. Using travel survey data and routing software, we propose a method to analyze the Trip Completion Potential (TCP) of cycling, defined as the rate of completable trips within a 30-minute travel time cutoff and the changes in value given different Levels of Traffic Stress (LTS). Overall, our analysis found that cycling can be a viable transport option for short and medium-length trips for many individuals and trip purposes. However, both the urban form and provision of a convenient cycling network play a vital role, especially in suburban areas, as seen in the decrease in TCP of cycling at different LTS levels. We conclude our analysis by proposing some key guidelines to achieve the objectives defined by the City of Toronto in an equitable manner.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".