Social capital and adolescent smoking: an application of a cross-classified multilevel model
Bibliographic record
Abstract
Background The aetiology of adolescent substance use is multifactorial. Particularly, the effects of the interface of family, school, and neighborhood, is ill understood, and the concept of social capital may be useful in exploring this interrelationship. The present study aims to consider these contextual social capital influences on adolescent cigarette smoking. Methods The data comes from the 2005/6 Flemish Health Behavior among School-aged Children survey, which is part of the international Health Behaviour in School-Aged Children survey: a WHO Collaborative Cross-National Study. Self-completion questionnaires were administered in schools using a standardized research protocol. Social capital was assessed by structural and cognitive components of family social capital, a four-factor school social capital scale and a cognitive neighborhood social capital scale. A non-hierarchical multilevel model was fitted in MLwiN 2.25, with 5169 adolescents nested within a cross-classification of 41 schools and 204 neighborhoods. Results A cross-classified logistic regression model showed significant variation in adolescent regular smoking between schools, but not between communities. Only structural family social capital and cognitive school social capital variables (vertical and trust) negatively related to regular smoking (p < 0.05). Additionally, a truly contextual effect was found for vertical social capital on the school level (p < 0.05). No interactions between socio-economic status indicators and social capital variables were found. Conclusions The present study suggests that previously observed community-level effects on adolescent smoking may be a consequence of unmeasured confounding. Distinguishing nested contexts of social capital is important because their associations with smoking differ. School policy makers should invest in vertical ties between pupils and teachers because they have a protective effect on smoking.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".