A measure that relates to elementary school children's risk of injury: the supervision attributes and risk-taking questionnaire (SARTQ)
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to examine the psychometric properties of the supervision attributes and risk-taking questionnaire (SARTQ), which is a new measure of caregiver supervision and child risk-taking that applies to elementary school children 7-10 years of age. METHODS: Using a prospective design, scores on the SARTQ were related to children's recent and long-term history of injuries and to parents' supervision scores that were derived based on measuring their home supervision practices over 8 weeks. RESULTS: Subscale scores on the SARTQ related differentially to measures of supervision and child injury scores, providing support for the criterion validity of this new measure. CONCLUSION: Results from this initial test of the SARTQ suggest that it holds promise as a measure that is relevant to understanding injury risk for elementary school children.
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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 | 0.003 | 0.001 |
| 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 | 0.001 |
| 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".