Road Safety Audits and major P-3 freeway projects: quantifying the findings
Bibliographic record
Abstract
Road Safety Audits (RSAs) provide an independent review process that has increasingly been incorporated into the development process for (typically) large-scale highway construction projects throughout Canada. While RSAs are thought to be a cost-effective means to improve safety, little is known empirically about the net outcome. This study involved comparing the RSA findings from three large-scale Public-Private-Partnership (P-3) freeway projects with similar fundamental characteristics (e.g., functional classification, rural setting, RSA team, and project budget). The RSA findings from different project stages (design, pre-opening, and post-opening) were synthesized and contrasted to develop a better understanding of the safety impacts being generated by the review process. These findings provide a benchmark that will eventually allow for the estimation of the net benefits of RSAs considering both costs and savings derived from collision mitigation. The results of the study indicate that the RSA process evolved from stage to stage, and from project to project.
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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 | 0.117 | 0.323 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".