Adverse Childhood Experiences and Adult Criminality: How Long Must We Live before We Possess Our Own Lives?
Bibliographic record
Abstract
BACKGROUND: Empirical research associated with the Kaiser Permanente and Centers for Disease Control and Prevention Adverse Childhood Experiences (ACE) Study has demonstrated that ACE are associated with a range of negative outcomes in adulthood, including physical and mental health disorders and aggressive behavior. METHODS: Subjects from 4 different offender groups (N = 151) who were referred for treatment at an outpatient clinic in San Diego, CA, subsequent to conviction in criminal court, completed the ACE Questionnaire. Groups (nonsexual child abusers, domestic violence offenders, sexual offenders, and stalkers) were compared on the incidence of ACE, and comparisons were made between the group offenders and a normative sample. RESULTS: Results indicated that the offender group reported nearly four times as many adverse events in childhood than an adult male normative sample. Eight of ten events were found at significantly higher levels among the criminal population. In addition, convicted sexual offenders and child abusers were more likely to report experiencing sexual abuse in childhood than other offender types. CONCLUSIONS: On the basis of a review of the literature and current findings, criminal behavior can be added to the host of negative outcomes associated with scores on the ACE Questionnaire. Childhood adversity is associated with adult criminality. We suggest that to decrease criminal recidivism, treatment interventions must focus on the effects of early life experiences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".