Examining If Changes in the Type of School-Based Intramural Programs Affect Youth Physical Activity over Time: A Natural Experiment Evaluation
Bibliographic record
Abstract
(1) School-based physical activity programs such as intramurals provide youth with inclusive opportunities to be physically active, yet we know little about how types of intramurals (e.g., team and individual sports) may contribute to youth MVPA. This research aims to evaluate how real-world changes in types of intramurals available in schools impact youth physical activity over time. (2) This study used three years of longitudinal school- and student-level data from Ontario schools participating in year 5 (2016-2017), year 6 (2017-2018) and year 7 (2018-2019) of the COMPASS study. Data on types of intramural programs from 55 schools were obtained, baseline demographic characteristics were measured and data on physical activity and sport participation were collected on a sample of 4417 students. Hierarchical linear mixed regression models were used to estimate how changes in the type of intramurals associate with youth MVPA over time. (3) Regardless of participation, adding individual and team intramurals was significantly and positively associated with female MVPA in Y6. (4) The indirect, but positive relationship between adding individual and team intramurals and female MVPA may be explained by other characteristics of the school environment that are conducive to female MVPA.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".