Development of a Traffic Safety Action Plan for the City of Saskatoon
Bibliographic record
Abstract
A Traffic Safety Action Plan (TSAP) is currently being developed for the City of Saskatoon. A TSAP is defined as a scientific, data-driven, four to five year comprehensive safety document that is designed to identify a jurisdiction's areas of safety concern known as areas, establish target collision reduction goal(s), provide network screening results, and general countermeasures and strategies for each chosen emphasis area. This TSAP will help the City of Saskatoon allocate their limited resources to a manageable number of emphasis areas to maximize the benefits for safety investment and generate the greatest safety improvement. The objective of the paper is to describe the development of a municipal-level TSAP for the City of Saskatoon. The study starts with the selection of emphasis areas using the most recent ten years of collision data (2001-2010). The results of the stakeholder workshop and the chosen emphasis areas (i.e., Intersections, Aggressive Driving, Distracted Driving, Vulnerable Road Users, Impaired Driving, Young Drivers and Older Drivers) will then be discussed. Preliminary network screening of the chosen emphasis areas will be presented, and will be followed by the selection of countermeasures/strategies and target goals in the future. (A) For the covering abstract of this conference see ITRD record number 201310RT334E.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".