Are There Early Risk Markers for Pedophilia? A Nationwide Case-Control Study of Child Sexual Exploitation Material Offenders
Bibliographic record
Abstract
Kelly M. Babchishina*, Michael C. Setoa, Seena Fazelb & Niklas Långströmca Forensic Research Unit, The Royal's Institute of Mental Health Researchb Department of Psychiatry, University of Oxfordc Department of Medical Epidemiology and Biostatistics, Karolinska Institute; and Department of Neuroscience, Uppsala UniversityCorrespondence should be addressed to Kelly M. Babchishin, Forensic Research Unit, The Royal’s Institute of Mental Health Research, 1145 Carling Ave, Ottawa K1Z 7K4, Canada. E-mail: Kelly.Babchishin@theroyal.caSupplemental data for this article can be accessed here.Although prior research suggests associations between parental characteristics and later sexual offending in offspring, possible links between early pregnancy-related factors and sexual offending remain unclear. Early risk markers unique to sexual offending, however, may be more prominent among sexual offenders with atypical sexual interests, such as individuals involved with child sexual exploitation material (CSEM; also referred to as child pornography). We examined the prospective association between parental and pregnancy-related risk markers and a behavioral indicator of pedophilic interest, CSEM offending. All 655 men born in Sweden and convicted of CSEM offending between 1988 to 2009 were matched 1:5 on sex, birth year, and county of birth in Sweden to 3,928 controls without sexual or nonsexual violent convictions. Paternal age (adjusted odds ratio [AOR] = 1.3, 95% confidence interval [CI] [1.1, 1.7]), parental education (AOR = 0.8, 95% CI [0.6, 0.9]), parental violent criminality (AOR = 2.9, 95% CI [2.2, 3.8]), number of older brothers (AOR = 0.8, 95% CI [0.6, 0.9] per brother), and congenital malformations (AOR = 1.7, 95% CI [1.2, 2.4]) all independently predicted CSEM convictions. This large-scale, nationwide study suggests parental risk markers for CSEM offending. We did not, however, find convincing evidence for pregnancy-related risk markers, with the exception of congenital malformations and having fewer older brothers.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".