Exploring the Prospective Relationship Between School Safety Climate and Adolescent Depressive Symptoms: A Multilevel Approach
Bibliographic record
Abstract
This article examines if the school safety climate is associated with depressive symptoms in students, beyond direct violence exposure. 5,262 students from 71 secondary schools were followed annually. We assessed safety climate using the Socio-educational environment questionnaire and derived school-level (Level 2; average of student scores) and student-level (Level 1; group mean-centered scores) safety measures, and depressive symptoms using the Center for Epidemiological Studies-Depression. Multilevel regression analysis revealed that individual perceptions of safety strongly correlate with depressive symptoms, especially among girls, while no significant link was found at the school level. This study shows that personal perceptions of safety are better predictors of depressive symptoms than the general safety climate of schools, emphasizing the importance of further research to explore how insecurity affects students differently.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".