Cyber bullying behaviors among middle and high school students.
Bibliographic record
Abstract
Little research has been conducted that comprehensively examines cyber bullying with a large and diverse sample. The present study examines the prevalence, impact, and differential experience of cyber bullying among a large and diverse sample of middle and high school students (N = 2,186) from a large urban center. The survey examined technology use, cyber bullying behaviors, and the psychosocial impact of bullying and being bullied. About half (49.5%) of students indicated they had been bullied online and 33.7% indicated they had bullied others online. Most bullying was perpetrated by and to friends and participants generally did not tell anyone about the bullying. Participants reported feeling angry, sad, and depressed after being bullied online. Participants bullied others online because it made them feel as though they were funny, popular, and powerful, although many indicated feeling guilty afterward. Greater attention is required to understand and reduce cyber bullying within children's social worlds and with the support of educators and parents.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".