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Record W3090871763 · doi:10.35502/jcswb.144

Measuring intimate partner violence risk: A national survey of Canadian police officers

2020· article· en· W3090871763 on OpenAlex
Michael Saxton, Peter G. Jaffe, Anne-Lee Straatman, Laura Olszowy, Myrna Dawson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Community Safety and Well-Being · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of GuelphWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRisk assessmentDomestic violencePsychologySuicide preventionOccupational safety and healthSurvey researchPoison controlEnvironmental healthCriminologyPolitical scienceApplied psychologyMedicineComputer securityLaw

Abstract

fetched live from OpenAlex

This study examined the role of police in addressing intimate partner violence (IPV) and the type of strategies they apply across Canada based on a national survey of officers. The focus was on an examination of the types of structured tools Canadian police officers report using in their risk assessment strategies. The results suggest that Canadian police officers are reporting frequent engagement in risk assessments across jurisdictions. The survey findings indicate variability across provinces in the types of risk assessment tools police officers are using. Implications for future research include exploring specific provincial and territorial police risk assessment processes and the challenges in engaging in risk assessments.

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.

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)0.006
metaresearch head score (Gemma)0.001
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 score0.451
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.313
Teacher spread0.245 · 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