Behavioural Consistency and Offender Characteristics: Investigating Modus Operandi Patterns in Serial Stranger Sex Offences
Bibliographic record
Abstract
Case linkage is a statistical technique which connects multiple sexual assault cases to a single perpetrator and holds promise for informing criminal investigations. Further, examining the behaviours executed most consistently across serial offences committed by a given offender is crucial to linking offences. The current study investigated behavioural consistency in a sample of 49 male serial stranger sexual offenders responsible for 147 offences. For each offence, four crime aspects were identified: 1) pre-crime facilitators, 2) victim selection and characteristics, 3) approach and attack methods, and 4) crime scene characteristics. Consistency between and within each crime series and across offender types based on background characteristics was examined. Results indicated a high degree of behavioural consistency across all crime aspects. Behaviours occurring prior to the offence were particularly useful in establishing consistent offending patterns. The implications of these findings in the context of police investigations and their utility for clinical practice are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".