Examining Antisocial Behavioral Antecedents of Juvenile Sexual Offenders and Juvenile Non-Sexual Offenders
Bibliographic record
Abstract
In prospective longitudinal studies of juvenile offenders, the presence of multiple developmental pathways of antisocial behaviors has consistently been identified. An "antisocial" type of juvenile sex offender (JSO) has also been identified; however, whether antisocial JSOs follow different antisocial pathways has not been examined. In the current study, differences in antisocial pathways within JSOs and between JSOs and juvenile non-sex offenders (JNSOs) were examined. Data on Canadian male incarcerated adolescent offenders were used to identify whether behavioral antecedents differed within JSOs and between JSOs (n = 51) and JNSOs (n = 94). Using latent class analysis (LCA), three behavioral groups were identified. For both JSOs and JNSOs, there was a Low Antisocial, Overt, and Covert group. Overall, there were important within-group differences in the behavioral patterns of JSOs, but these differences resembled differences in the behavioral patterns of their JNSO counterpart. Risk factors including offense history, abuse history, and family history were more strongly associated with the Overt and Covert groups compared with the Low Antisocial group. Implications for JSO assessment practices were discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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 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".