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Record W3191559101 · doi:10.1177/00938548211033631

Predictive Properties of the Ontario Domestic Assault Risk Assessment (ODARA) in a Northern Canadian Prairie Sample

2021· article· en· W3191559101 on OpenAlexaffabout
Jennifer hegel, Karen D. Pelletier, Mark E. Olver

Bibliographic record

VenueCriminal Justice and Behavior · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRecidivismPoison controlDomestic violenceInjury preventionIndigenousOccupational safety and healthSuicide preventionHuman factors and ergonomicsRisk assessmentDemographySample (material)MedicineGeographyPsychologyEnvironmental healthPsychiatryComputer securitySociology

Abstract

fetched live from OpenAlex

This study examined the predictive properties of the Ontario Domestic Assault Risk Assessment (ODARA) in a large Canadian, predominantly Indigenous, sample from a geographic region with the highest rates of intimate partner violence (IPV) in the country. A random stratified sample of 300 men (92.7% Indigenous) court adjudicated for an IPV offense was drawn from six Northern Saskatchewan Royal Canadian Mounted Police detachment regions. The ODARA was rated from police records and recidivism data were obtained via official criminal records over a mean 4.7-year follow-up. ODARA scores had small to moderate predictive accuracy (AUC/C = .58–.67) for IPV and other recidivism outcomes in the aggregate sample and Indigenous subsample. E/O index analyses demonstrated that the ODARA Ontario norms overpredicted IPV recidivism at high scores but underpredicted it at lower mid-range scores. Implications for use of the ODARA to assist frontline police personnel in IPV risk assessment and management 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.046
GPT teacher head0.328
Teacher spread0.282 · 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

Citations15
Published2021
Admission routes2
Has abstractyes

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