Child Restraint Use in Canadian Provinces With and Without Legislation in 2010
Bibliographic record
Abstract
OBJECTIVES: When used correctly, child safety seats reduce the risk of injury to a child passenger compared to seat belts. The objectives of this study are to (1) describe restraint use among Canadian children ages 4-8 years in 2010; (2) compare child safety seat use between provinces with new legislation (post-2006), old legislation (pre-2006), and without legislation; and (3) compare child safety seat use rates from 2006 to 2010. METHODS: Roadside observational surveys of child restraint use were performed in 2006 and 2010 using a nationally representative stratified sample. Proportions of restraint use, correct use (i.e., child safety seats and booster seats) in 4- to 8-year-old children was examined between 3 groups: provinces with new legislation (i.e., child safety seat legislation that included implementation of specific legislation for booster seat use for child passengers ages 4-8 years), old legislation, and no legislation. RESULTS: There were 4048 children observed as passengers in motor vehicles. In provinces with new legislation, 84 percent (95% confidence interval [CI], 72.2-90.8) of children were restrained compared to 94.9 percent (95% CI, 93.0-96.7) in provinces with old legislation, and 81.8 percent (95% CI, 77.3-86.3) in provinces without legislation. Correct use of child restraint was 54.1 percent (95% CI, 48.0-60.3) in provinces with new legislation, 29.5 percent (95% CI, 25.9-33.2) in provinces with old legislation, and 52.0 percent (43.0-61.0) in provinces without legislation in 2010. CONCLUSION: The findings from this study suggest that child safety seat legislation has an impact on restraint use in Canada. Despite the increase in rates of child safety seat use in provinces with new legislation and stable rates in provinces with old legislation, use rates remain low. Injury prevention strategies including further surveillance, interventions, and enforcement of restraint use in children are important to decrease motor vehicle related injury and death.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".