Cyberbullying in High Schools: A Study of Students' Behaviors and Beliefs about This New Phenomenon
Why this work is in the frame
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Bibliographic record
Abstract
This study explores high school students' beliefs and behaviors associated with cyberbullying. Specifically, it examines this new phenomenon from the following four perspectives: (a) What happens after students are cyberbullied? (b) What do students do when witnessing cyberbullying? (c) Why do victims not report the incidents? and (d) What are students' opinions about cyberbullying? Data were collected from 269 Grade 7 through 12 students in 5 Canadian schools. Several themes have emerged from the analysis, which uncovers some important patterns. One finding is that over 40% would do nothing if they were cyberbullied, and only about 1 in 10 would inform adults. Students feel reluctant to report cyberbullying incidents to adults in schools for various reasons, which are discussed in depth.
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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) | 0.001 | 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) | 0.002 | 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 it