Are we there yet? Canada's progress towards achieving road safety vision 2010 for children travelling in vehicles
Bibliographic record
Abstract
This study examines safety seat use among Canadian children and evaluates child safety seat use relative to the national policy for child occupant safety, Road Safety Vision 2010. Using a probability sample, roadside observations of car safety seat use were collected from May to October of 2006 for 13,500 children aged from birth to 9 years in 10,084 vehicles at 182 sites in nine Canadian provinces and one territory. Observations revealed that 89.9% of Canadian children were restrained in some type of restraint. However, only 60.5% of these children were restrained in the correct safety seat. When comparing rates of correct use across provinces, results were not significantly different in provinces with booster seat legislation and those without this legislation. This data may be useful for healthcare practitioners and policy makers to develop interventions aimed at increasing appropriate car safety seat use for children in Canada.
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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 | 0.001 | 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) | 0.000 | 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".