Cyber bullying behaviors among middle and high school students.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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