PW 0373 Evaluation of the vision zero school safety zones program in the city of toronto- policy makers and researchers working together
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The City of Toronto adopted its Vision Zero Road Safety Plan in July 2016, with its focus on eliminating motor vehicle collisions that result in death and serious injuries. The safety plan emphasizes a collaborative and integrative approach, involving multiple stakeholders. One of the Plan’s six areas of emphasis is on school children. Stakeholders from public health, the public school board, the police, a not-for- profit organization and academic researchers have worked with the City of Toronto’s Transportation Services Division to identify a package of interventions to create School Safety Zones. New interventions include physical environment changes, enforcement activities, education and support from a school traffic management facilitator. The Plan is intended to be evidence-based and data-driven. Therefore, it is essential that policy makers and researchers work together to develop appropriate evaluation strategies. Several challenges to policy makers and researchers working together exist; most of which can be overcome using a collaborative process. For example, funding cycles and priorities of granting agencies to fund academic research may not match the timelines and priorities of policy makers. Researchers prefer evidence-based priority setting and random selection to enhance scientific validity, whereas policy makers also consider political priorities and community interests. Although researchers would ideally like to maximize sample size, policy makers often have fiscal restraints. The definition of meaningful and valid outcome measurements is a challenge. Fatal and severe collisions are relatively rare, so proxy measures must be agreed upon prior to the evaluation. Regular meetings of stakeholders will help ensure evaluation that is meaningful to policy makers and scientifically sound. This process will lead to a strategy to be used by City of Toronto, Transportation Services to evaluate the effectiveness of their school zone safety interventions and can provide a model for future evaluations of Vision Zero Road Safety Plan interventions.
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.
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 | 0.002 | 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 it