Investigating Distance Halo Effects of Mobile Photo Enforcement on Urban Roads
Bibliographic record
Abstract
This paper investigates the distance halo effects of mobile photo enforcement (MPE) on urban roads in Edmonton, Alberta, Canada. Speed data were recorded at various distances upstream and downstream of nine locations during four MPE site visits and at the corresponding times in 4 days without enforcement. Data collection was performed during the summer months of 2015. A two-sample t-test was used to compare the speed limit violations during the enforcement site visits and during the corresponding times without enforcement. The results of the analysis indicate that distance halo effects existed at all study locations and that significant reductions in speed limit violations occurred. The authors concluded that, on average, if an MPE unit were deployed eight times during a week for 22 h (equivalent to 2.7 h per visit), the unit would produce a drop in violations ranging from 10% to 17% over a distance of 500 m upstream and downstream of the enforcement unit. In addition, the number of enforcement hours per week and the average hours per visit were found to be strongly correlated with the reduction in speed limit violations. The findings of this study can help enforcement agencies significantly increase the coverage of MPE programs and their expected safety benefits.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".