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 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".