Sex Differences in Associations of School Connectedness With Adolescent Sexual Risk‐Taking in Nova Scotia, Canada
Bibliographic record
Abstract
BACKGROUND: Associations of lower school connectedness have been seen with adolescent sexual risk behaviors, but little is known about gender differences with respect to these relationships. Understanding any such differences could contribute to better supporting the school environment to promote youth sexual health. METHODS: We used provincially representative cross-sectional data from 1415 sexually active students in grades 10 to 12 in Nova Scotia, Canada, to determine whether lower school connectedness was associated with students' sexual risk behaviors using multivariate logistic regression, stratifying by sex. RESULTS: In boys, lower connectedness was associated with three risk behaviors, having ≥ 2 partners in the previous year (odds ratio [OR] 1.07; 95% confidence interval [CI] 1.01-1.13), no condom use at last intercourse (OR 1.06; 95% CI 1.01-1.12), and having unplanned intercourse due to substance use (OR 1.09; 95% CI 1.03-1.15). No such associations were seen in girls. CONCLUSIONS: These results demonstrate that gender differences may exist for associations of school connectedness and sexual risk behaviors; connectedness may be more important for boys than for girls in this area of adolescent health. Educators should consider gender differences when designing interventions to maximize youth sexual health through school-based interventions. Further research on school connectedness and risk-taking should examine genders separately.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".