Evaluating the need for secured bicycle parking in Montréal
Bibliographic record
Abstract
"Montréal is considered one of the most cyclable cities in North America, and yet every year thousands of bicycles are stolen across the city. Theft of bicycles can cause financial burdens on cyclists and can dissuade people from cycling. One potential solution is to invest in bicycle parking, including secured parking facilities. Indeed, secured bicycle parking has proven to be a good solution to decrease bicycle theft in other cities, especially in northern Europe. In fact, secured bicycle parking deters bicycle theft by making it harder for thieves to access the bicycles and by adding surveillance (camera or guard). This research tries to identify if Montréal could benefit from secured bicycle parking facilities, if Montréal’s cyclists desire them, what characteristics they would like them to have and if they would be willing to pay to use the service. To do so, a survey of 95 questions was created to explore the thoughts of cyclists in Montréal on the subject. To better analyse the surveys’ responses, respondents have been categorized in four different cyclists’ typologies: leisure, summer, occasional and dedicated cyclists. Dedicated cyclists have been identified the most likely to use secured bicycle parking. Across all typologies, the top three most desired secured parking features are being low-cost, close to final destinations and with protection from bad weather. It was found that cyclists in Montréal would be willing to pay an average of 1,5 $/day for the service, however, to ensure equity between all income groups, this paper recommends providing this service for free. Furthermore, the respondents stated that parking should be located within a 4-minute walk (maximum) from users’ final destinations. Taken together, this report concludes that Montréal could benefit from secured bicycle parking and includes specific policy recommendations to support the implementation of this service across the city"@eng
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".