Awareness of bicycle light use of young adults
Bibliographic record
Abstract
Helmet use amongst bicyclists has been well documented in recent literature. Helmet use is not the only measure cyclists can take to reduce their chance of crashes. Many places, in addition to mandating helmet use by law for youths, also require bicycle lights to be used under low-light conditions (i.e. during sunrise, during sunset and at night). The aim of this study was to investigate the awareness of bicycle light use amongst young adults, with respect to the legalities and also utility of lights while cycling. An anonymous survey was developed and circulated to young adults in Canada, Ireland and the United States of America. A total of 112 individuals completed the survey. Only 13% of individuals had an unsatisfactory knowledge of bicycle light use. As knowledge is the first step towards advocating for new measures, young adults seem well -versed with respect to bicycle light use and may be able to be targeted to increase bicycle light use. Frequency of commute was related to the knowledge of bicycle light use; those who commuted more regularly were more knowledgeable. This study, however, was composed primarily of young adults residing in Canada. Future studies could investigate knowledge among young adults who reside in a region that more regularly commutes using a bicycle, to see whether this trend holds.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".