Pedestrian injury at signalised midblock versus signalised intersections locations in Toronto, Canada
Bibliographic record
Abstract
Background Signalised intersections are the ‘gold standard’ providing the safest environment for pedestrian crossings; however, it is unknown whether the safety effects of traffic signals are maintained at midblock locations. Aims/Objectives/Purpose To evaluate injury outcomes of pedestrian collisions at signalised midblock compared to signalised intersection locations. Methods Police-reported pedestrian collision data from 2000–2009 in Toronto, Canada were obtained. Multinomial logistic regression analyses were used to assess the relationship between a four level categorical outcome of injury severity and signalised midblock versus signalised intersection locations. Models were stratified by age and adjusted for road type. Results Of 8479 collisions analysed, 88% of collisions were at signalised intersections. Almost ¼ of child collisions occurred at midblock versus 11% in adults. Over 25% of signalised midblock collisions in seniors resulted in major or fatal injury. The odds of major injury were 2.21 (95% CI 1.32 to 3.70) in children and 2.11 (95% CI 1.57 to 2.83) in adults. The odds of fatal injury were 4.37 (95% CI 1.92 to 9.97) in seniors at signalised midblock versus intersection locations. Significance Traffic signals at midblock locations do not provide the same degree of protection against major and fatal collisions as they do at intersections. The increased likelihood of a fatal injury in seniors at signalised midblock locations may indicate difficulty in usage or ineffectiveness in slowing down traffic. The barriers to safe use of signalised midblock crossings need to be identified to ensure effectiveness for all ages.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".