The social-ecological model of cyberbullying: Digital media as a predominant ecology in the everyday lives of youth
Bibliographic record
Abstract
While cyberbullying has been recognized as a critically important social problem, a void remains regarding the role of digital media. To address this gap, we propose the social-ecological model of cyberbullying, an expanded model that builds on Bronfenbrenner’s ecological systems theory (EST) and expands Swearer and Espelage’s social-ecological model of bullying. A strength of the proposed model is the addition of the digital context as a new ecology in the everyday lives of youth, which is closely interconnected with all the other systems. Furthermore, the model incorporates digital-specific factors within each ecological system of the original EST model. This provides scholars with a holistic model that they can test, finetune, and expand. A practical implication of the model is that it can guide the creation and implementation of effective and age-appropriate cyberbullying prevention and intervention approaches because it considers in the chronosystem life phases, life transitions, historical events, and crises.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".