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Record W4409508937 · doi:10.1177/00938548251333800

Comparative Analysis of Intimate Partner Violence Perpetrators According to their Referral Type: Self-Referred, Legally Mandated, and Formally Pressured

2025· article· en· W4409508937 on OpenAlexafffund
Marie Dodier-Lemay, Laurie Arseneault, Fabienne Glowacz, Caroline Dugal, Natacha Godbout, Claudia Savard, Audrey Brassard

Bibliographic record

VenueCriminal Justice and Behavior · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversité LavalUniversité du Québec à MontréalUniversité du Québec à Trois-RivièresUniversité de Sherbrooke
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDomestic violenceReferralSuicide preventionPsychologyInjury preventionHuman factors and ergonomicsPoison controlDiversity (politics)Occupational safety and healthPsychiatryClinical psychologyMedicineSocial psychologyMedical emergencyFamily medicineLawPolitical science

Abstract

fetched live from OpenAlex

Intimate partner violence (IPV) is a major public health issue with long-lasting consequences, necessitating effective treatments to disrupt its intergenerational transmission. However, the common one-size-fits-all approach in IPV programs may fail to acknowledge the diversity among perpetrators. This study compared three types of IPV perpetrators entering treatment: self-referred, legally mandated, and formally pressured. Among 1,302 men surveyed, self-referred men were generally older, more educated, and reported more clinical symptoms than those in the other groups. They appeared more ready to change and less influenced by social desirability biases. Legally mandated men reported fewer minor IPV behaviors, but more severe behaviors compared with self-referred men. They seemed to minimize or deny their behavior, failing to acknowledge their problem with violence. Formally pressured men exhibited mixed characteristics. They appeared to be motivated by the fear of losing custody of their children. These findings underscore the need for tailored therapeutic approaches.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.058
GPT teacher head0.389
Teacher spread0.331 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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