Beyond the Quarter Mile: Examining Travel Distances by Walking and Cycling, Montreal, Canada
Bibliographic record
Abstract
Interest in active transportation -especially walking and cycling -is growing within urban planning and transportation circles as a solution to many of the environmental and congestion issues plaguing many cities.This paper focuses on how far people are willing to walk or cycle for different trip purposes in Montréal, Canada and how travel distances vary spatially and by individuals' travel purpose and socioeconomic characteristics.This research uses the 2003 Montréal Origin-Destination Survey (O-D Survey) to calculate the network distance traveled by pedestrians and cyclists and to obtain travel and socioeconomic characteristics for each individual.Whereas much walking distance literature focuses on distance to transit, this paper is focused on walking and cycling trips where a second transit mode is not the intended destination.Primarily, the paper reveals that median walking distances recorded in the O-D survey (650 meters) are greater than the commonly-accepted distance or catchment area of 400 meters, and that there are a variety of personal built environment factors that influence these distances.While no widely-held standard exists for cycling, the analysis reveals a median distance of around two kilometers with a high degree of variation in distances.These findings will guide planners, designers, developers, and policy makers when promoting for greater levels of walking and cycling and suggests future research directions within this field.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".