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Record W4253034789 · doi:10.32920/ryerson.14649555

Behavioural Consistency and Offender Characteristics: Investigating Modus Operandi Patterns in Serial Stranger Sex Offences

2021· preprint· en· W4253034789 on OpenAlexaff
Sandra Oziel

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsConsistency (knowledge bases)PsychologyContext (archaeology)CriminologySocial psychologySample (material)Sexual assaultSex offenderHuman factors and ergonomicsPoison controlComputer scienceMedicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.105
GPT teacher head0.341
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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