How Does Land Use Influence Cyclist Route Choice? Geospatial Analysis of Commuter Routes and Cycling Facilities
Bibliographic record
Abstract
This paper contributes to the body of literature on the built environment and non-motorized travel behaviors by examining the role of land use in cyclist route choice. Using data from a sample of cyclists in Montreal, Quebec, Canada who responded to a web-based survey, the routes for those who were traveling for work or school purposes and used cycling facilities were examined and these actual taken routes were compared with the corresponding shortest-path routes with respect to the adjacent land use. By using a variety of geospatial analysis tools, different methods to quantify land use, including area- and count-based measures, were examined. A series of statistical tests and models revealed that commuter cyclists prefer to ride through areas that are generally less busy and have lower potentials for conflicts. This includes routes that have adjacent residential as well as resource and industry uses and paths that are near water.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".