Reducing speeding via inanimate police presence
Bibliographic record
Abstract
Research Summary The present research uses data from a police‐directed field study to explore the effects of police presence on speeding in two large cities in British Columbia, Canada. As part of the study, an inanimate but realistic‐appearing police cut‐out (“Constable Scarecrow”) was strategically positioned along roadways while motorist speed was measured using a radar‐recording device. The analyses of the multisite evaluation reveal that the presence of the cut‐out can reduce speeding when deployed along arterial roadways. Policy Implications Traffic collisions are a leading cause of death and nonfatal injuries for people worldwide. A well‐documented contributor to traffic collisions is speed. Controlling speed has thus become a priority for government, police, and community groups across the world. The findings from the present research demonstrate that police can reduce speeding via their inanimate presence. This is the first known study to evaluate the effects of an inanimate but realistic‐appearing police cut‐out on motorist behavior: a sustainable, low‐cost, and easily implementable intervention for communities of all sizes in all places.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".