A MULTI-LEVEL ANALYSIS OF THE EFFECT OF SCHOOL EXPERIENCES ON INJURY AND LEISURE ACTIVITIES AMONG CANADIAN CHILDREN
Bibliographic record
Abstract
ABSTRACT. Using Canadian data from the 1998 Cross-National Survey on Health Behaviors in School-Aged Children, the present study examined the effects of school experiences on injury and leisure activities among Canadian students. Health outcomes were classified into two categories: injury (with and without medical treatment) and leisure activities (time spent on television and computer games, frequency of exercise, and hours of exercise). Multi-level analysis of cross-sectional data (from Grades 6 to 10) indicated that injury among students increased slightly over time and students increasingly lived an inactive life as they grew older. Student injury was not closely associated with either individual characteristics or school experiences. Gender emerged as the strongest student-level predictor of leisure activities. Characteristics of effective schools in which students spent less time on display screens included (a) positive peer influence, (b) fair school roles, and (c) positive sense of belonging to school. School experiences highlighted positive sense of belonging to school as the strongest school-level predictor of physical activities. UNE ANALYSE A NIVEAUX MULTIPLES DES EFFETS DES EXPERIENCES SCOLAIRES DES ENFANTS CANADIENS SUR LES BLESSURES ET LES ACTIVITES DE LOISIR RESUME. A l'aide de donnees canadiennes tirees de l'enquete transnationale de 1998 sur les comportements lies a la sante des jeunes d'âge scolaire, la presente etude a examine les effets des experiences scolaires sur les blessures et les activites de loisir chez les eleves canadiens. Les consequences pour la sante ont ete classees dans deux categories: les blessures (avec et sans traitement medical) et les activites de loisir (le temps consacre a la television et aux jeux informatiques, la frequence de l'exercice et les heures d'exercice). L'analyse a niveaux multiples des donnees transversales (de la 6e a la 10e annee) a revele que les blessures chez les eleves ont legerement augmente au fil du temps et que les eleves menaient une vie de moins en moins active a mesure qu'ils vieillissaient. Les blessures n'etaient pas etroitement liees aux caracteristiques individuelles ou aux experiences scolaires. Le sexe des eleves s'est revele le principal indicateur previsionnel des activites de loisir. Les caracteristiques des ecoles actives dans lesquelles les eleves passaient moins de temps devant des ecrans comprenaient notamment (a) une influence positive des pairs, (b) un reglement d'ecole equitable et (c) un sentiment positif d'appartenance a l'ecole. Les experiences scolaires ont fait ressortir ce sentiment positif d'appartenance comme le principal indicateur previsionnel des activites physiques a l'ecole.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".