Cyberbullying from the perspective of I3 theory: The role of instigating triggers and impelling forces
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
Theoretical frameworks remain a necessity for developing targeted interventions, providing an explanatory framework, and determining factors that predict success or failure. Cyberbullying research, however, remains a largely atheoretical endeavour. Qualitative research has been heralded as a necessary next step to expand theoretical frameworks in this field. The current study utilized thematic analysis to investigate high school students’ (Mage = 16.71, SDage = .56) beliefs regarding the reasons why students cyberbully others. Analysis of responses indicated situational, social-relational, and offender-based reasons for cyberbullying. I3 theory (I-cubed-theory) was used as a posteriori framework to interpret these results, demonstrating its adaptability to this field of study. This study is the first qualitative research to utilize I3 theory as a framework for 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.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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