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
Although recent research has demonstrated significant links between involvement in cyber bullying and various internalizing difficulties, there exists debate as to whether these links are independent of involvement in more traditional forms of bullying. The present study systematically examined the association between involvement in cyber bullying, as either a victim or a bully, and both depressive symptomatology and suicidal ideation. Self-report data were collected from 399 (57% female) Canadian adolescents in grades 8-10 (mean age = 14.2 years, SD = .91 years). Results indicated that involvement in cyber bullying, as either a victim or a bully, uniquely contributed to the prediction of both depressive symptomatology and suicidal ideation, over and above the contribution of involvement in traditional forms of bullying (physical, verbal, relational). Given the ever increasing rate of accessibility to technology in both schools and homes, these finding underscore the importance of addressing cyber bullying, with respect to both research and intervention, as a unique phenomenon with equally unique challenges for students, parents, school administrators and researchers alike.
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 | 0.000 |
| 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