Parental and perinatal risk factors for sexual offending in men: a nationwide case-control study
Bibliographic record
Abstract
BACKGROUND: Prior studies suggest parental and perinatal risk factors are associated with later offending. It remains uncertain, however, if such risk factors are similarly related to sexual offending. METHOD: We linked socio-demographic, family relations, and perinatal (obtained at birth) data from the nationwide Swedish registers from 1973 to 2009 with information on criminal convictions of cases and control subjects. Male sex offenders (n = 13 773) were matched 1:5 on birth year and county of birth in Sweden to male controls without sexual or non-sexual violent convictions. To examine risk-factor specificity for sexual offending, we also compared male violent, non-sexual offenders (n = 135 953) to controls without sexual or non-sexual violent convictions. Predictors included parental (young maternal or paternal age at son's birth, educational attainment, violent crime, psychiatric disorder, substance misuse, suicide attempt) and perinatal (number of older brothers, low Apgar score, low birth weight, being small for gestational age, congenital malformations, small head size) variables. RESULTS: Conditional logistic regression models found consistent patterns of statistically significant, small to moderate independent associations of parental risk factors with sons' sexual offending and non-sexual violent offending. For perinatal risk factors, patterns varied more; small for gestational age and small head size exhibited similar risk effects for both offence types whereas a higher number of older biological brothers and any congenital malformation were small, independent risk factors only for non-sexual violence. CONCLUSIONS: This nationwide study suggests substantial commonalities in parental and perinatal risk factors for the onset of sexual and non-sexual violent offending.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".