Direct and indirect bully‐victims: differential psychosocial risk factors associated with adolescents involved in bullying and victimization
Bibliographic record
Abstract
Abstract The present study examined psychosocial risk factors that differentiated direct and indirect bully‐victims from bullies, victims and uninvolved adolescents. A total of 7,290 (3,756 girls) students (ages 13–18 yr) from a region of Southern Ontario, Canada, completed a number of self‐report measures to determine the relation between direct and indirect bullying and victimization and several psychosocial risk factors, including normative beliefs about antisocial acts, angry‐externalizing coping, social anxiety, depression, self‐esteem, temperament, attachment, parental monitoring and peer relational problems. ANCOVA and logistic regression analyses indicated that indirect bully‐victims and victims were similar in demonstrating greater internalizing problems and peer relational problems than indirect bullies and uninvolved participants. Furthermore, adolescents involved in indirect bullying (bullies, bully‐victims) reported a higher level of normative beliefs legitimizing antisocial behaviour and less parental monitoring (males only) than indirect victims and uninvolved participants. Only normative beliefs legitimizing antisocial behaviour distinguished direct bully‐victims and bullies from victims and uninvolved adolescents. Results illuminate the distinct characteristics of direct and indirect bully‐victims; theoretical and clinical implications are discussed. Aggr. Behav. 32:551–569. 2006. © 2006 Wiley‐Liss, Inc.
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".