Typologies of sexually motivated abductions: a latent class analysis
Bibliographic record
Abstract
To date, sexually motivated abductions have not received as much attention from researchers in comparison to the acts of abduction and sexual assault alone. Further, the majority of research that is conducted on abductions focuses solely on child victims, creating a gap in the literature. The current study was set forth to identify qualitatively different subgroups of offenders who commit sexually motivated abductions. Using victim, crime, and offender characteristics taken from sexual abduction cases (n = 1288), a latent class analysis was conducted. Results from the latent class analysis revealed that four subgroups of sexually motivated abductors exist: Convenience Opportunist, Strategic Opportunist, Child Opportunist, and Familiar Opportunist. In addition, bivariate analyses were run to test the latent class solution with different characteristics; results suggest that these subgroups of sexually motivated offenders may not be dependent on some victim lifestyle characteristics. These results provide evidence that there are qualitatively different subgroups of offenders who commit sexually motivated abductions, which may be useful for law enforcement when conducting investigations.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".