Bicycling crash circumstances vary by route type: a cross-sectional analysis
Bibliographic record
Abstract
Background: Widely varying crash circumstances have been reported for bicycling injuries, likely because of differing bicycling populations and environments. We used data from the Bicyclists’ Injuries and the Cycling Environment Study in Vancouver and Toronto, Canada, to describe the crash circumstances of people injured while cycling for utilitarian and leisure purposes. We examined the association of crash circumstances with route type. Methods Adult cyclists injured and treated in a hospital emergency department described their crash circumstances. These were classified into major categories (collision vs. fall, motor vehicle involved vs. not) and subcategories. The distribution of circumstances was tallied for each of 14 route types defined in an earlier analysis. Ratios of observed vs. expected were tallied for each circumstance and route type combination. Results Of 690 crashes, 683 could be characterized for this analysis. Most (74%) were collisions. Collisions included those with motor vehicles (34%), streetcar (tram) or train tracks (14%), other surface features (10%), infrastructure (10%), and pedestrians, cyclists, or animals (6%). The remainder of the crashes were falls (26%), many as a result of collision avoidance manoeuvres. Motor vehicles were involved directly or indirectly with 48% of crashes. Crash circumstances were distributed differently by route type, for example, collisions with motor vehicles, including “doorings”, were overrepresented on major streets with parked cars. Collisions involving streetcar tracks were overrepresented on major streets. Collisions involving infrastructure (curbs, posts, bollards, street furniture) were overrepresented on multiuse paths and bike paths. Conclusions These data supplement our previous analyses of relative risks by route type by indicating the types of crashes that occur on each route type. This information can guide municipal engineers and planners towards improvements that would make cycling safer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".