Bully/victim relationships and school violence: evaluating patterns of aggression
Bibliographic record
Abstract
There were five major goals of this research project: (1) to estimate student victimization and bullying behaviour prevalence rates and gather general information about bully/victim activity in a medium sized Roman Catholic school board in rural Ontario, Canada; (2) to develop and initially validate an adolescent based scale for measuring vengeful cognitions; (3) to examine the relationships between vengeance and bully/victim involvement among students; (4) to expand the current knowledge base regarding youth aggression patterns in terms of bully/victim group membership; and (5) to develop a post hoc model of vengeance. In total, 1066 grade 7, 8, 9 and 10 students completed a questionnaire that measured aggression, anger, self-esteem, and vengeance in addition to surveying their recent experiences with peer-abuse. Study 1 estimated prevalence rates for victimization and bullying behaviour in a self-selected sample. In Study 2, a unidimensional twelve-item School Vengeance Cognition Scale (SVCS) with strong internal reliability was developed and validated. Confirmatory Factor Analysis attested to the one-factor structure of the SVCS. Correlations among variables indicated that vengeful-attitudes and cognitions were positively related to physical and verbal aggression, anger, hostility, anger experience, school cynicism, and destructive expression, and negatively correlated with self-esteem and positive coping. In Study 3, a hypothesized association between victimization and vengeance was not supported while bullying behaviour correlated positively with revenge. Aggression patterns across bully/victim groups were also examined. Finally, a three-factor model of vengeance that predicted 55% of the variance in vengeance scores was derived using multiple regression and confirmatory analyses. Findings are discussed in terms of school violence and counselling.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".