Transactional links between adolescents’ and friends’ victimization during the first two years of secondary school: The mediating role of likeability and friendship involvement
Bibliographic record
Abstract
Abstract The goals of this study were to examine to what extent lower likeability at the group level and lower friendship involvement can explain the bidirectional links between adolescents’ own and their friends’ victimization over time. We tested these processes by applying a cross‐lagged path model to a sample of 621 adolescents. Data were collected at four time points over the two first years of secondary school. Participants were asked to identify same grade friends within their school; classroom peer nominations were used to assess participants’ likeability as well as participants’ and friends’ level of peer victimization. Results showed bidirectional associations between adolescents’ own and their friends’ victimization by peers within the first year of secondary school. Moreover, the relation between adolescents’ own victimization at the end of the first year and their friends’ victimization next year was mediated by decreased adolescents’ likeability at the group level. Inversely, their friends’ victimization at the end of the first year predicted lower levels of adolescents’ own likeability over time, which in turn predicted adolescents’ own subsequent levels of victimization. Friends’ victimization also predicted adolescents’ lower friendship involvement during the first year, which in turn predicted decreased likeability, and ultimately higher levels of victimization.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".