Looking Beyond Assumptions to Understand Relationship Dynamics in Bullying
Bibliographic record
Abstract
To account for the complex relationships and processes that constitute the phenomenon of bullying, it is critical to understand how students and their parents and teachers conceptualize traditional and cyberbullying. Qualitative data were drawn from a mixed methods longitudinal study on cyberbullying. Semi-structured interviews were held with Canadian students in grades 4, 7, and 10 in a large urban school board, and their parents and teachers. To account for the complexity and interactions of different systems of relationships, the purpose of the current article is to examine how students and their matched parents and teachers understand traditional and cyberbullying. Central to participants' understanding of traditional and cyberbullying was whether they considered bullying to represent harmful relationship dynamics. Three main assumptions emerged as shaping participants' understanding of bullying and appeared to obscure the deep relationship processes in bullying: (a) assumptions of gender in bullying, (b) type of bullying-comparing traditional and cyberbullying, and (c) physical bullying as disconnected from relationship dynamics. It is essential that assessment, education, and prevention and intervention strategies in traditional and cyberbullying be informed by the inherent relationships in bullying and be implemented at multiple levels of relationships and broader social systems.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".