Evaluating the need for secured bicycle parking across cyclist typologies
Bibliographic record
Abstract
Concerns about bicycle theft can act as a barrier to cycling uptake. A promising solution to prevent theft is secured bicycle parking, which offers more protection than regular on-street bicycle racks through secured access, or the presence of an attendant. As cities begin to invest in this infrastructure, practitioners must make difficult decisions about which types of facilities to install, where to install them, and how much to charge for their use. Therefore, this study draws on a large-scale cycling survey (n = 1806) distributed in Montréal, Canada to explore how secured bicycle parking needs vary across different cyclist typologies. To do so, factor-cluster analysis was conducted to generate cyclist typologies. Then the behaviors and secured bicycle parking needs of these different cyclists were established. Four distinct cyclist types emerged: Leisure Cyclists, Summer Cyclists, Occasional Cyclists, and Dedicated Cyclists. Dedicated cyclists were most interested in secured bicycle parking, while occasional cyclists were the least. Leisure cyclists, on the other hand, are willing to pay and walk the most for secured bicycle parking. Across typologies, the top three most important characteristics of secured bicycle parking are (1) being free or low cost, (2) having secured access, and (3) being close to their destination. Respondents are most interested in secured bicycle parking near their work and metro stations. The results from this study can inform practitioners and researchers about the secured bicycle parking needs of different types of cyclists, and in doing so help in the planning for such facilities.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".