Joint Trajectories of Peer Cyber and Traditional Victimization in Adolescence: A Look at Risk Factors
Why this work is in the frame
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Bibliographic record
Abstract
This study aimed to identify joint trajectories of peer cyber and traditional victimization from ages 13 to 17 and individual, family, peer, and school risk factors associated with group membership. The sample was composed of 1,194 adolescents (54.2% girls). Cyber and traditional victimization were assessed at ages 13, 15, and 17. The results first revealed a low/increasing and a high/decreasing trajectories for cybervictimization and a low/decreasing and a moderate/chronic for traditional victimization. Conditional probabilities suggested that cybervictims had a high probability of being victims on school grounds, whereas traditional victims were not necessarily the target of cybervictimization. Four joint trajectory groups were also identified. With the low victimization group as the reference category, the results revealed that different sets of predictors were associated with membership in the three other joint trajectory groups. The results are discussed in relation to intervention and prevention strategies.
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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 | 0.000 |
| 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 it