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Record W4394951451 · doi:10.1002/bsl.2660

Trophy, souvenir, or simple theft? Taking items from the victim in sexual homicide

2024· article· en· W4394951451 on OpenAlexaff
Megan Walter, Éric Beauregard, Julien Chopin

Bibliographic record

VenueBehavioral Sciences & the Law · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTrophyHomicideSexual assaultPoison controlSuicide preventionInjury preventionMedical emergencyCriminologyOccupational safety and healthHuman factors and ergonomicsComputer securityPsychologyMedicineComputer scienceLawPolitical science

Abstract

fetched live from OpenAlex

Although most people have heard the terms 'souvenirs', 'trophies', and 'mementos', discussed in books and movies on the true crimes of sexual murderers, limited research has delved into the phenomenon of theft in sexual homicide (SH). Using a sample of 762 SH cases coming from the Sexual Homicide International Database, the current study examines the crime-commission process of the pre-crime, crime, and post-crime phases of sexual homicide offenders (SHOs) who engaged in theft during a SH. Additionally, this study seeks to determine if a specific type of SHO engages in this behaviour over others. Results from the sequential logistic regression indicate that victims who are 16 years or older, were strangers to the SHO, and were sex workers were more likely to be victims of theft. Additionally, results indicate that the presence of sadism made it more likely the SHO would engage in theft from the victim and/or crime scene. Findings suggest there is a group of SHOs who engage in theft not for monetary purposes but due to the paraphilia of the offender. These findings can inform the police investigation of these crimes.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.196
GPT teacher head0.457
Teacher spread0.261 · 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.

Study designNot applicable
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

Citations7
Published2024
Admission routes1
Has abstractyes

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