Bibliographic record
Abstract
The purpose of this study was to examine the victim-bully cycle in middle school and to identify student and school characteristics that contributed to the cycle of bullying, using cross-sectional data from the New Brunswick School Climate Study (N = 6,883 in grade 6 and N = 6,868 in grade 8). The results of a multivariate, multilevel analysis clearly indicated that the relationship of bully to victim was reciprocal. At the student level, gender, affective condition, and physical condition contributed to the victim-bully cycle in both grades. The number of siblings contributed to the cycle of bullying in grade 8. Gender, affective condition, and the number of siblings were more characteristics of bullies than victims, whereas physical condition was more a characteristic of victims than bullies. The victim-bully cycle at the school level has rarely been reported in the literature. This study suggests that the cycle of bullying was present in several aspects of school life. School size and discipline climate contributed to the victim-bully cycle in both grades. Parental involvement contributed to the cycle of bullying in grade 6, whereas academic press contributed to the cycle of bullying in grade 8. Although discipline climate both helped victims and discouraged bullies, parental involvement and academic press discouraged bullies more than helped victims.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".