Examining Antisocial Behavioral Antecedents of Juvenile Sexual Offenders and Juvenile Non-Sexual Offenders
Bibliographic record
Abstract
Prior studies have indicated that that there is an “antisocial” type of juvenile sex offender (JSO) that resembles juvenile non-sex offenders (JNSOs). However, a single categorization of all antisocial JSOs may be too broad given that there are different types of antisocial behavior (e.g., authority conflict, overt, covert). To clarify potential differences between JSOs and JNSOs, different antisocial behavior patterns should be explored and compared between these two groups. This study examined data on Canadian male incarcerated adolescent offenders to identify whether behavioral antecedents differed within JSOs (n = 51), and between JSOs and JNSOs (n = 94). Latent class analysis identified three behavioral groups. For both JSOs and JNSOs there was a Low Antisocial, Overt, and Covert group. Risk factors including offence history, abuse history, and family history were more strongly associated with the Overt and Covert groups compared to the Low Antisocial group. Overall, there were important within-group differences in the behavioral patterns of JSOs, but these differences resembled differences within their JNSO counterpart. Clinical implications for responding to incarcerated JSOs with behavioral problems are 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) | 0.002 | 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".