COVID-19 and speeding: Results of population-based survey of ontario drivers
Bibliographic record
Abstract
INTRODUCTION: During COVID-19, increased speeding was observed in many jurisdictions. Yet, evidence is limited on what factors predicted increased speeding during the pandemic. This study's purpose was to examine speeding, and person and situation factors associated with increased speeding since the start of the pandemic. METHODS: An online panel survey sampled 1,595 drivers using sex, age, and region quota sampling and weighting to approximate the Ontario, Canada adult population. Measures included: (1) person factors: socio-demographics (age, sex, region); psychological trait of risk propensity (Competitive Attitudes Toward Driving Scale (CATDS)); psychological states (distress - general and COVID-19-related); and behaviors (kilometers driven, alcohol use, police stops and collisions); and (2) COVID-19-related situation factors: perceived changes in (traffic volume, police enforcement). RESULTS: 67.2% of respondents reported speeding; 7.2% reported increased speeding since the start of the pandemic. Bivariate analyses indicated that person factors of younger age, male sex, higher CATDS, higher distress, more alcohol use, more kilometers traveled, police stops, and collisions since the start of the pandemic were associated with increased speeding. Situation factor of perceived less traffic volume since the start of the pandemic was associated with increased speeding. Logistic regression analysis identified odds of reported increased speeding during the pandemic was significantly higher for drivers with higher scores on the CATDS, higher kilometers traveled, and more alcohol use during the pandemic. CONCLUSIONS: These findings suggest that higher risk propensity as well as the more kilometers driven and increased alcohol consumption were risk factors for increased speeding. PRACTICAL APPLICATIONS: COVID-19-related factors of lower traffic volume and enforcement are less predictive of increased speeding than driver personality and pandemic-related behaviors of more driving and drinking. Interventions to reduce speeding still need to focus on these person factors through education, enforcement, and strong sanctions for speeding.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".