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Record W2516946846 · doi:10.1177/0093854816667974

Appraising Risk for Intimate Partner Violence in a Police Context

2016· article· en· W2516946846 on OpenAlexaffabout
Sandy Jung, Karen Buro

Bibliographic record

VenueCriminal Justice and Behavior · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsMacEwan University
Fundersnot available
KeywordsRecidivismDomestic violenceContext (archaeology)PsychologyPredictive validityPoison controlHuman factors and ergonomicsSuicide preventionInjury preventionRisk assessmentOccupational safety and healthClinical psychologySocial psychologyMedical emergencyMedicineComputer securityGeographyComputer science

Abstract

fetched live from OpenAlex

This study examines the predictive accuracy of three risk assessment approaches for intimate partner violence (IPV) among a sample of 246 male perpetrators who were charged for offenses against their intimate partners. The sample was followed up for an average of 3.3 years, and any new general, violent, and IPV charges and convictions were recorded. The Ontario Domestic Assault Risk Assessment (ODARA) and a modified 14-item version of the Spousal Assault Risk Assessment Guide (SARA) demonstrated large effects in their ability to predict any reoffending or any violent reoffending and moderate predictive accuracy for IPV offending behaviors. The regionally used approach, Family Violence Investigative Report (FVIR), showed good predictive validity for any future offending but poorly predicted any of the violent-specific recidivism outcomes. Results of the study show that the ODARA was significantly better at predicting violence risk over the FVIR, but paired comparisons did not reveal statistical differences with the SARA.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.062
GPT teacher head0.383
Teacher spread0.320 · 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 designOther design
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

Citations42
Published2016
Admission routes2
Has abstractyes

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