Proximity to four bikeway types and neighbourhood-level cycling mode share of male and female commuters
Bibliographic record
Abstract
We studied 2011 cycling mode share at the census-tract level in Montréal and Vancouver, Canadian cities with relatively high mode shares and diverse bike infrastructure. We examined whether mode share variability, for all commuters and male and female commuters separately, was related to proximity to any bikeway, proximity to four bikeway types, slopes on routes to bikeways, or commute times. Cycling mode shares at the census-tract level varied from 0 to 20.4%. About a third of cycle commuters were female, but this proportion approached parity with males in census tracts with mode shares of 7% and higher. A one-kilometer closer proximity to any bikeway was associated with four times higher cycling mode share. Proximity to cycle tracks was associated with higher cycling mode shares in both cities. Other bikeway types did not have similar associations in the two cities, and the pattern of results suggested that the networks formed may have been more important than specific bikeway characteristics. Uphill slopes to bikeways were associated with somewhat lower mode shares in bivariate analyses but not in adjusted models. Cycle commuting was most common in neighborhoods with intermediate average commute durations: 20 to 29 minutes. Our results suggest that cycle tracks and bikeways that form a connected network are associated with higher neighborhood cycling commute mode shares. These features appeared even more important to women, and their cycling (or not) was strongly related to overall cycling mode shares.
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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 | 0.000 | 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".