Cyberbullying among youth: A comprehensive review of current international research and its implications and application to policy and practice
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
Cyberbullying research is rapidly expanding with many studies being published from around the world in the past five or six years. In this article we review the current international literature published in English, with particular attention to the following themes: The relationship of cyberbullying to the more traditional face-to-face bullying, including differences and similarities; the impacts of cyberbullying on victims, bullies, schools, families, and communities; coping strategies for victims, schools, and parents; and solutions, both effective and ineffective. A focus of this article is evidence-based prevention and intervention strategies, which may be employed by educators, psychological service providers, and by parents to counter the problem of cyberbullying. Here we address the importance of school and home culture, modelling, curriculum development in information and communication technology (ICT) and social media, peer and bystander education, and other non-punitive approaches. We conclude with a discussion of implications on policy and practice and future research directions.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it