Measurement of Pedestrian Exposure to the Potential Dangers of Daily Activity-Travel Patterns in the Region of Montreal
Bibliographic record
Abstract
The objective of the present study is to elaborate and validate a measurement which would allow us to identify the circumstances and levels of pedestrian exposure to the potential dangers of daily activity-travel patterns in the region of Montreal. A review of the literature led us to construct three simple models and a composite model of exposure to traffic. The data were collected with the help of a daily diary of travel activities using a sample of pedestrians who went to work or to study or who returned to home. To calculate the distance, the length of walk, and the number of intersections crossed by a pedestrian, different Geographic Information Systems (GIS) were operated. Statistical analysis was used to determine the significance between a measure of exposure on the one hand, and the sociodemographic characteristics of the participants or their geographic location on the other hand. Our results indicate that the potential exposure to risk of road accidents differs according to where the pedestrian lives. We also stress the point that the fact of having been involved in a road accident did not appear to change the actions of pedestrians. For the covering abstract see ITRD E129315.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".