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Record W2095910843 · doi:10.1177/0886260507306566

Who Is Most at Risk for Intimate Partner Violence?

2007· article· en· W2095910843 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Interpersonal Violence · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDomestic violencePhysical abusePsychological abusePoison controlPopulationSexual abusePsychologyInjury preventionSuicide preventionOccupational safety and healthPsychiatryClinical psychologyMedicineDemographyEnvironmental health

Abstract

fetched live from OpenAlex

Whole population studies on intimate partner violence (IPV) have given contradictory information about prevalence and risk factors, especially concerning gender. The authors examined the 1999 Canadian General Social Survey data for gender patterns of physical, sexual, emotional, or financial IPV from a current or ex-partner. More women (8.6%) than men (7.0%, p = .001) reported partner physical abuse in general, physical IPV causing physical injury (p < .0001), sexual abuse (1.7% vs. 0.2%, p < .0001), and financial abuse (4.1% vs. 1.6%, p < .0001). There were no gender differences for partner emotional abuse. Significant risk factors after multivariate modeling for physical/sexual IPV were younger age, being divorced/separated or single, having children in the household, and poor self-rated physical health. These findings from a large, randomly generated data set further refine our understanding of the risk profile for IPV in the developed world.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.339
Teacher spread0.318 · 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