The impact of pedestrian countdown signals on pedestrian–motor vehicle collisions: a quasi-experimental study
Bibliographic record
Abstract
OBJECTIVE: To determine whether pedestrian countdown signals (PCS) reduce pedestrian-motor vehicle collisions in the city of Toronto, Canada. METHODS: A quasi-experimental study design was used to evaluate the effect of PCS on the number of pedestrian-motor vehicle collisions in the city of Toronto, from January 2000 to December 2009. Each intersection acted as its own control. We compared the number of pedestrian-motor vehicle collisions per intersection-month before and after the intervention. Stratified models were used to evaluate effect modification by pedestrian age, injury severity and location (urban vs inner suburbs). Poisson regression analysis with repeated measures (generalised estimating equations) was used to estimate the RR and 95% CI. RESULTS: The analysis included 9262 pedestrian-motor vehicle collisions at 1965 intersections. The RR of collisions after PCS installation was 1.014 (95% CI 0.958 to 1.073), indicating no statistically significant effect of PCS on collisions. There was no evidence to suggest effect modification between PCS and collisions by age, injury severity or location. CONCLUSION: The installation of PCS at 1965 signalised intersections in Toronto did not reduce the number of pedestrian-motor vehicle collisions at these intersections.
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".