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Record W4365516762 · doi:10.1177/00938548231166152

Target Selection and Crime Characteristics: A Comparison of Sexually Motivated Abduction Cases to Nonsexual Abduction Cases and Nonabduction Sexual Cases

2023· article· en· W4365516762 on OpenAlexaff
Éric Beauregard, Julien Chopin

Bibliographic record

VenueCriminal Justice and Behavior · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCommitPsychologyPoison controlHuman factors and ergonomicsInjury preventionLogistic regressionSuicide preventionSocial psychologyDevelopmental psychologyComputer securityMedical emergencyMedicineComputer science

Abstract

fetched live from OpenAlex

Abduction has been related to a more extensive violent criminal record, suggesting that it represents a risk for escalation in violence. As most research has investigated child abductions, the current study compares sexually motivated abductions ( n = 1,288) to nonsexually motivated abductions ( n = 270) and nonabduction sexual assaults ( n = 1,500) involving both children and adult women victims. Logistic regression analyses showed that compared with nonsexually motivated abductions, those that are sexually motivated are typically committed on victims who are single, while they are hitchhiking at night, and perpetrated in the offender’s car. Moreover, when compared with nonabduction sexual assaults, results show that individuals who commit sexually motivated abductions are more likely to use a con approach on a stranger victim, to use a weapon, restraints, inflict serious injuries, and penetrate vaginally the victim either in their residence or their car. Abduction cases are often characterized by instrumental violence and both children and adult women need to be prioritized.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.080
GPT teacher head0.384
Teacher spread0.304 · 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 designQualitative
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

Citations2
Published2023
Admission routes1
Has abstractyes

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