The prevalence of road rage: Estimates from Ontario.Canadian
Bibliographic record
Abstract
Background: “Road rage ” has increasingly generated public concern, however, the prevalence of this behaviour has not been available. We examine the prevalence and demographic correlates of road rage victimization and perpetration based on a population survey of adults in Ontario. Methods: Data are based on the CAMH Monitor, a repeated cross-sectional telephone survey of Ontario adults (n=1,395). The contribution of demographic factors to road rage was examined with logistic regression analysis. Results: About half of respondents (46.6%) were shouted at, cursed at or had rude gestures directed at them in the past year, and 7.2 % were threatened with damage to their vehicle or personal injury. Nearly a third of respondents (31.7%) admitted to shouting, cursing, etc. at someone, and 2.1 % threatened to hurt someone or damage their vehicle. Being a Toronto resident, being younger, and earning a higher income were associated with greater likelihood of being a victim of shouting, cursing and rude gestures; however, income was not associated with being threatened with vehicle damage or injury. The
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| 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) | 0.007 | 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 teacher head, 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".