Incorporating Highway Safety Factors into Provincial Highway Investment Decision-Making in Saskatchewan, Canada
Bibliographic record
Abstract
Network level highway investment normally considers infrastructure's current level of service and future demand based on forecasted traffic growth. Safety improvement initiatives are normally designed to address identified specific substantive safety concerns. It is often the case that substantive safety at highway locations may not correlate to nominal safety. Rural communities relying on low standard roads often feel that their safety concerns may not be adequately considered in the investment decision-making process. There may not be a quantitative relationship between road conditions and substantive safety, however, upgrading low standard roads will certainly improve their nominal safety and address public perception of road safety concerns. It is a challenge in decision-making to balance the investment needs of economic growth demand and community safety concerns. Saskatchewan has developed rural highway strategies to guide capital investment to maximize social and economic benefits. The strategies utilize a multifactor evaluation method to prioritize highway upgrading investment. In addition to economic and traffic considerations, quantifiable road safety factors reflecting both substantive and nominal safety are incorporated into the strategies. Successful incorporation of these factors most concerned for rural highways has made the strategies more acceptable to the public.
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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".