‘Under the radar’: Educators and cyberbullying in schools
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
Educators play an important role in preventing cyberbullying and encouraging positive online behaviour. In this article we report on the educator portion of a study of cyberbullying at two large, technology-rich secondary schools in Canada. We discuss 17 educators’ experiences with cyberbullying, their knowledge of social networking technology, the priority they place on preventing cyberbullying, and the remedies they suggest. Qualitative analyses of taped interview responses to 16 open-ended questions revealed that they were unaware of the extent of cyberbullying among their students and although they saw prevention as a priority, and were able to pose possible solutions, no policies or programs had been implemented, even by the younger teachers, who were more technologically savvy. Nor were the educators interested in learning the results of the student portion of our research, preferring instead that cyberbullying remain under their radar.
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 | 0.000 |
| 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) | 0.006 | 0.001 |
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