Predictors of Nonstandard Helmet Use Among San Francisco Bay–Area Motorcyclists
Bibliographic record
Abstract
OBJECTIVE: The use of helmets that do not comply with safety standards is common in California. The objective of this study was to describe the use of these nonstandard helmets among San Francisco Bay-area (SFBA) motorcyclists and to identify personal and motorcycle characteristics that are associated with the use of nonstandard helmets. METHODS: A survey of 860 SFBA motorcyclists was conducted. Log-binomial regression was used to estimate risk ratios to compare probabilities of nonstandard helmet use. RESULTS: Fifteen percent of motorcyclists reported wearing a nonstandard helmet sometimes or often. BMW riders had the lowest use of nonstandard helmet (5%) and Harley-Davidson riders had the highest use (51%). Among non-Harley-Davidsons, riders of cruiser-style motorcycles were 3.1 times as likely to wear a nonstandard helmet as riders of motorcycles of other styles. African American riders were more than twice as likely to use nonstandard helmets compared to riders with other self-reported race. DISCUSSION: Behavioral countermeasures are needed to improve motorcycle helmet choice in California. This study identified riders of Harley-Davidsons and riders of cruiser-style motorcycles of other brands as potential targets of interventions.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".