Exploring Links to Unorganized and Organized Physical Activity During Adolescence
Bibliographic record
Abstract
There is limited research on participation context in studies of physical activity correlates during adolescence. Using an ecological approach, this study explored the association of gender; socioeconomic status (SES), weight status, and physical education enjoyment with participation in organized and unorganized physical activity contexts in a representative sample of Canadian adolescents. Drawing on data from the National Longitudinal Survey of Children and Youth (Cycle 3), we conducted multiple logistic regression analyses to model the associations among the variables of interest. Girls participated less frequently in unorganized physical activities than boys (adjusted odds ratios [AORs] ranging from 0.57 to 0.65, 95% confidence intervals [CIs] range: 0. 46-0.72 to 0.52-0.81). Adolescents in the middle and high SES categories participated more in organized physical activity than their peers in the low SES category (AOR = 1.40-1.87, CI = 1.06-1.84 to 1.41-2.47). Obese adolescents were generally less active than their overweight and normal weight counterparts, particularly in unorganized physical activity contexts (AOR = 0.63-0.66, CI = 0.43-0.92 to 0.44-0.99). Physical education enjoyment was consistently correlated with participation in organized and unorganized physical activity when all variables were considered (AOR = 1.58-3.98, CI = 1.22-2.05 to 3.14-5.03).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".