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Record W2163359850 · doi:10.1177/1077801206292681

Partner Violence Against Women With Disabilities

2006· article· en· W2163359850 on OpenAlexaffabout
Douglas A. Brownridge

Bibliographic record

VenueViolence Against Women · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDomestic violenceOddsPoison controlPsychologyIntimate partnerInjury preventionSuicide preventionHuman factors and ergonomicsOccupational safety and healthMarital statusSexual violencePsychiatryClinical psychologyMedicineDemographyMedical emergencyPopulationCriminologyEnvironmental healthLogistic regressionSociology

Abstract

fetched live from OpenAlex

Using a representative sample of 7,027 Canadian women living in a marital or common-law union, this investigation examined the risk for partner violence against women with disabilities relative to women without disabilities. Women with disabilities had 40% greater odds of violence in the 5 years preceding the interview, and these women appeared to be at particular risk for severe violence. An explanatory framework was tested that organized variables based on relationship factors, victim-related characteristics, and perpetrator-related characteristics. Results showed that perpetrator-related characteristics alone accounted for the elevated risk of partner violence against women with disabilities. Stakeholders must recognize the problem of partner violence against women with disabilities, and efforts to address patriarchal domination and male sexual proprietariness appear crucial to reducing their risk of partner violence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.875
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.272
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), 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

Citations293
Published2006
Admission routes2
Has abstractyes

Explore more

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