Cyberbullying: Adolescents’ Experiences, Responses, and Their Beliefs about Their Parents’ Recommended Responses
Bibliographic record
Abstract
A total of 116 adolescents, ranging in age from 15 to 19 years, completed a questionnaire that assessed their experiences with cyberbullying, what they would do if they were a victim of cyberbullying, and what they believed their parents would recommend they do if they were a victim of cyberbullying. The proportion of adolescents who reported ever being cyberbullied was larger than the proportion of adolescents who reported ever cyberbullying another person. In addition, the adolescents reported that they were more frequently cyberbullied by same-sex peers than by opposite-sex peers. Although the adolescents’ preferred response to a cyberbully was congruent with the response they believed their parents would recommend (i.e., ignore the cyberbully), the adolescents anticipated that they and their parents would disagree on the individuals from whom the adolescents should seek advice if they were cyberbullied. Specifically, whereas the adolescents anticipated that their parents would want to be the primary advice-providers, the adolescents indicated that they would be more likely to seek advice from their friends than their parents or teachers if they were a victim of cyberbullying.
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.
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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".