© Birkhäuser Verlag, Basel, 2009 The relationship of schools to emotional health and bullying
Bibliographic record
Abstract
Objectives: To examine the extent to which school climate and school pressure could predict other aspects of adolescents’ lives, most particularly their emotional health and bullying. Furthermore, the study sought to investigate if these relation-ships were consistent across countries. Methods: Participants were 11-, 13-, and 15-year-olds from 26 European countries/regions, Canada, the United States, and Israel. Participants completed surveys focusing on health be-haviours and lifestyles, using a contextual framework. Using cluster analytic techniques, three clusters were created varying on school pressure and perceived school climate. These clusters were then examined using variables not used in the cluster-ing. Results: Students in the cluster having the most positive re-lationships to school outcomes, including academic achieve-ment, truancy, teacher and peer support, also had the most positive emotional health and the lowest incidence of bullying. Similarly, those in the poorest cluster in terms of school also had the poorest outcomes in terms of emotional health and bullying. Conclusions: These relatively small but significant associations suggest that schools may have a small role in supporting chil-dren’s emotional well-being and ameliorate the presence of bullying.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.257 | 0.150 |
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".