Evaluation of Safe Kids Week 2004: Age 4 to 9? It’s Booster Seat Time!
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of a national one week media campaign promoting booster seat use. DESIGN: Pre-test, post-test design based on nationally representative random digit dialing telephone survey, with control for exposure to campaign. SETTING: Canada. SUBJECTS: Parents of children aged 4-9 years. INTERVENTIONS: During a one week campaign in May 2004, information on booster seat use was distributed via a national media campaign, retail stores, medical clinics, and community events. Information included pamphlets with guidelines for booster seat use, as well as a growth chart (designed by Safe Kids Canada) to assist parents in determining if their child should be using a booster seat. Assessing seat belt fit was described in detail on the growth chart. MAIN OUTCOME MEASURES: Knowledge, attitudes, and self-reported behaviors regarding booster seat use. RESULTS: Respondents in the group exposed to the campaign were twice as likely to report using a booster seat with lap and shoulder belt for their child (47%), compared to those in the pre-test (24%) and the unexposed (23%) groups (p<0.001). However, only small differences in general knowledge regarding booster seat use were found between the groups. CONCLUSIONS: A one week national media campaign substantially increased self-reported use of booster seats. Parents did not remember details of the campaign content, but did remember implications for their own child.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".