Does proximity to physical activity infrastructures predict maintenance of organized and unorganized physical activities in youth?
Bibliographic record
Abstract
Physical activity (PA) infrastructures can provide youth chances to engage in PA. As determinants of organized and unorganized PA (OPA and UPA) may differ, we investigated if proximity to PA infrastructures (proximity) was associated with maintenance of OPA and UPA over 3 years. Youth from New Brunswick, Canada (n = 187; 10-12 years at baseline) reported participation in OPA and UPA every 4 months from 2011 to 2014 as part of the MATCH study. Proximity data were drawn from parent's questionnaires. Proximity scores were divided into tertiles. Kaplan-Meier and Cox proportional hazard models were used to assess associations between proximity and maintenance of OPA and UPA. There were no crude or adjusted differences in average maintenance of participation in OPA [mean number of survey cycle participation (95%CI) was 6.6 (5.7-7.5), 6.3 (5.5-7.1), and 5.8 (5.1-6.6)] or UPA [6.8 (6.2-7.4), 5.9 (5.3-6.5), and 6.6 (5.9-7.3)] across low, moderate, and high tertiles of proximity, respectively. Findings suggest that proximity does not affect maintenance of participation in OPA or UPA during adolescence. Other environmental aspects may have a greater effect. Further research is needed before conclusions can be made.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".