School Social Fragmentation, Economic Deprivation and Social Cohesion and Adolescent Physical Inactivity: A Longitudinal Study
Bibliographic record
Abstract
OBJECTIVES: To examine the independent influence of school economic deprivation, social fragmentation, and social cohesion on the likelihood of participating in no physical activity among students. METHODS: Data are from a large-scale longitudinal study of schools based in disadvantaged communities in Quebec, Canada. Questionnaires were administered every year between 2002 and 2008 among n = 14,924 students aged 12 to 18 from a sample of 70 schools. Cross-sectional and longitudinal analyses were conducted. Multilevel modeling was utilized to account for the clustering of students within schools. Schools were categorized as being low, moderate or high economic deprivation, social fragmentation and social cohesion. Those who indicated that they do no participate in any physical activity during the week were identified as being physically inactive. RESULTS: In baseline multilevel cross-sectional analyses, adolescents attending schools in the highest (compared to the lowest) levels of socioeconomic deprivation and social fragmentation were more likely to be physically inactive (OR = 1.33, 95% CI = 1.03, 1.72; and OR = 1.24, 95% CI = 0.98, 1.56, respectively). Conversely, students attending schools with the highest cohesion were less likely to be physically inactive (OR = 0.78, 95% CI = 0.61, 0.99). In longitudinal analysis, physically active students who attended schools with the highest social fragmentation were more likely to become physically inactive over two years (OR = 1.65, 95% CI = 1.09, 2.51). CONCLUSION: The school socioeconomic environment appears to be an important contextual influence on participation in no physical activity among adolescents. Following adolescents beyond two years is necessary to determine if these environments have a lasting effect on physical activity behavior.
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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 | 0.003 |
| 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".