Bibliographic record
Abstract
Bus safety in Australia was benchmarked against Canada and the United States. The analysis highlights that the bus fatality rate in Australia (on a per vehicle-kilometre basis) is about half that in the United States or Canada. While this is encouraging, more disaggregate analyses highlight areas where safety can be improved. Buses experience high fatality rates than motor vehicles overall, with this primarily due to their incompatibility with passenger vehicles and pedestrians. Compared to other countries, Australia has a substantially worse safety performance with school buses, especially for collisions involving pedestrians. In fact, the fatality rate of school-age pedestrians killed in Australian school bus accidents was more than four times that in the United States and nearly double the Canadian rate. Population-based fatality rates for passengers on urban route or intercity bus services are shown to be upwards of 10 times those in the United States and Canada. When bus passengers and occupants of other vehicles are considered, intercity buses generated fatality rates more than double those in comparable countries. Mini-buses may be responsible for a disproportionate number of casualties in some states compared to other types of buses. The paper concludes by identifying several research initiatives that would help to provide a foundation for the objective and effective allocation of resources targeted to improve bus safety. Language: en
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".