Driver Knowledge and Beliefs About Antilock Brake Systems: Have Preconditions for Behavioral Adaptation Been Met?
Bibliographic record
Abstract
Some studies suggest that the benefits of antilock brake systems (ABS) may be offset through behavioral adaptation, such as driving faster or following closer. Whether preconditions for behavioral adaptation exist was examined by investigating driver knowledge and beliefs about ABS. Telephone interviews were conducted throughout Quebec early in 1999 with principal drivers of a stratified random sample of 404 drivers with currently registered light-duty vehicles, registered to the same person for at least 18 months. The response rate was 82 percent of 492 reached. Only medium-range and high-end 1990-1995 vehicles, for which ABS was either standard equipment or unavailable, were selected. The protocol involved mostly open questions that encouraged respondents to reveal their knowledge and beliefs with minimal prompting. The results indicated an important lack of understanding, on the part of a majority of drivers, regarding the functioning and use of ABS. This varied from an inability to identify conditions in which ABS is favorable or unfavorable to serious misconceptions; about 25 percent were wrong about whether their vehicle was ABS equipped. Cognitive preconditions for behavioral adaptations—sometimes increased prudence—were found for a minority of this sample, and there may be a relationship between a low level of knowledge and the perceived possibility of driving faster with these brakes. There appears to be a case for improved public and dealer-delivered information on the advantages and disadvantages of ABS in different driving conditions, which if balanced should not increase unsafe behavioral adaptation.
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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 | 0.012 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".