Potential risks and user preferences of helmet-sharing program provided by Vancouver’s Mobi bike-share program
Bibliographic record
Abstract
Background: Mobi is a bike-sharing program in Vancouver, BC that provides helmets for use with each bike. There is little research documenting risks associated with helmet-sharing, but an evidence review has shown that there is the potential for transmission of diseases that are known or presumed to be transmitted via fomites. This study attempted to ascertain public opinion of helmet-sharing and whether concern over the cleanliness of shared helmets affected likelihood of wearing them. Method: A survey was conducted to determine if there is a relationship between concern with helmet cleanliness and likelihood of wearing shared helmets. The researcher conducted surveys in-person at randomly chosen Mobi docking stations. An online (SurveyMonkey) survey was also distributed using Facebook, Twitter, Reddit and email. Results: Chi-square tests performed using NCSS determined that there was a statistically significant association between helmet use on personal bikes and use of Mobi helmet when riding Mobi bikes (p=0.00029). There was also an association between whether users found cleanliness the most important factor in their decision to wear the Mobi helmet (of cleanliness, aesthetics, legal requirement, safety and comfort/fit) and likelihood of wearing the Mobi helmet (p=0.02038). There was no association found between level of concern for cleanliness of the helmet and likelihood of wearing it (p=0.54995). Conclusions: Based on the results, there is an association between concern with the cleanliness of shared helmets are and how likely users are to wear them. Users that were most concerned about safety were more likely to use the Mobi helmet during every ride. Those that were most concerned about cleanliness were least likely to wear the Mobi helmet. However, this study also concluded that some users chose not to wear the provided helmets for reasons other than concern for cleanliness. Further research is required to determine how this will affect the health and safety of Mobi Bike users.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".