Opinions, attitudes and driving experiences of car and racing 'enthusiasts': Results of the Ontario Car and Racing Club survey
Bibliographic record
Abstract
In recent years, car club and racing websites and forums have become an increasingly popular way for car enthusiasts to access racing and car club news, chat-rooms and message boards. However, no North American research has been found that has examined opinions and driving experiences of car and racing enthusiasts. The purpose of this study was to examine car club members’ opinions about and experiences with various aspects of driving, road safety and traffic legislation, with a particular focus on street racing. A web-based questionnaire (Survey Monkey) was developed using the expert panel method and was primarily based on validated instruments or questions that were developed from other surveys. The questionnaire included: 1) driver concerns regarding traffic safety issues and legislation; 2) attitudes regarding various driving activities; 3) leisure-time activities, including club activities; 4) driving experiences, including offences and collisions; and 5) socio-demographic questions. The survey was pre- tested and piloted. Electronic information letters were sent out to an identified list of car clubs and forums situated in southern Ontario. Car club participants were invited to fill out the questionnaire. This survey found that members of car clubs share similar concerns regarding various road safety issues with samples of Canadian drivers, although a smaller percentage of car club members are concerned about speeding-related driving. Car club members had varied opinions regarding Ontario’s Street Racers, Stunt and Aggressive Drivers Legislation. The respondents agreed the most with the new offences regarding not sitting in the driver’s seat, having a person in the trunk, or driving as close as possible to another vehicle, pedestrian or object on or near the highway without a reason. The majority disagreed with police powers of impoundment and on-the-spot licence suspensions. About three quarters of respondents reported no collisions or police stops for traffic offences in the past five years. Of those who had been stopped, the most common offence was reported as speeding. This study is the first in Canada to examine car club members’ opinions about and experiences with various aspects of driving, road safety and traffic legislation. Given the ubiquity of car clubs and fora in Canada, insights on members’ opinions and practices provide important information to road safety researchers.
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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 | 0.000 |
| 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 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".