The Nature and Frequency of Cyber Bullying Behaviors and Victimization Experiences in Young Canadian Children
Bibliographic record
Abstract
As access to technology is increasing in children and adolescents, there are growing concerns over the dangers of cyber bullying. It remains unclear what cyber bullying looks like among young Canadian children and how common these experiences are. In this study, we examine the psychometric properties of a measure of cyber bullying behaviors and victimization experiences. We also examine the frequency of these behaviors and experiences among fifth- and sixth-grade Canadian children at the beginning ( n = 714) and end ( n = 638) of a school year. Children’s cyber bullying behaviors and victimization experiences were relatively stable across the school year and were highest for sixth-grade students who reported greater access to and use of technology. Cyber bullying behaviors representing joking around were endorsed more frequently than aggressive types of behaviors (i.e., spreading rumours or posting embarrassing pictures online). Implications for school-based prevention efforts are discussed.
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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 | 0.001 | 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".