Scootering on: An investigation of children’s use of scooters for transport and recreation
Bibliographic record
Abstract
Non-motorised scooters have increased significantly in popularity over the last few years in New Zealand, following similar trends in the US, Australia, Canada and Europe. Non-motorised scooters are an important source of recreation, transport and exercise and children of all ages enjoy riding them to and from school and in skate parks. \nAlong with the increase in popularity and use of the scooters, New Zealand is also experiencing a considerable increase in the numbers of injuries to children, with a notable spike in ACC claims in the 2011-12 year. Whilst most of the injuries are moderate – dislocations, fractures, lacerations and soft-tissue injuries – an increase in the number of severe injuries, and at times, even fatalities is also evident. Boys tend to be injured more frequently than girls and the median age for injury is nine years. Most injuries occur at home, with public roads the next most likely location. \nInternational literature shows similar trends world-wide. Numbers of scooter injuries are escalating and an intervention to minimise harm and reduce risk is considered imperative in all regions. The evidence shows that children are not wearing protective equipment (such as helmets) when travelling on a non-motorised scooter and there is no legal requirement for them to do so. Elbow and knee pads – and even footwear – were conspicuously absent amongst children observed in fieldwork undertaken for this project. \nChildren routinely use basic scooters for activities unsuited to their design and on terrain that poses further risks. It was also evident that children scootering to school were not subject to the same regulations as those cycling to school and there appears to be a general lack of awareness of the risks associated with scootering. We therefore propose the following recommendations as means by which we might minimise the risks and reduce harm to children: \no Amend the current cycle helmet legislation to include the riders of all wheeled recreational devices, irrespective of the age of the rider; \no Introduce school policies requiring that helmets and footwear are worn when scootering to and from school; \no Implement a minimum age for scootering to and from school; \no Extend the coverage of existing school training programmes on road safety in general and safe scootering in particular; \no Require compulsory distribution of point-of-sale information packs on the risks of scooters and the protective equipment options available; \no Ensure continued funding of current community resources and training initiatives \no Further research on scooter accidents and associated risk factors
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".