Vision Zero for Queensland School Students: Transferring Developmental & Cognitive Research into Road Safety Policy and Practice
Bibliographic record
Abstract
The last decade has seen a rapid increase in the use of mopeds and scooters in some cities where they have traditionally been uncommon. One such city is Brisbane, the capital city of the Australian State of Queensland, where a 50cc moped may be ridden on a car licence, while riders of larger scooters require a motorcycle licence. The first study reported here observed stationary powered two-wheelers (PTWs) in designated parking areas at six-monthly intervals from August 2008. Over one third of all PTWs observed were either mopeds (22%) or larger scooters (14%), while the majority were motorcycles (64%) (n = 2037). Focus groups were then held to explore riders’ perspectives on safety and transport planning issues. Parking availability, traffic congestion, cost, time-efficiency were frequently mentioned motivating factors. Moped riders were younger and less experienced and less likely to have undertaken or value rider training, and less likely to wear protective clothing.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".