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Record W2135959514 · doi:10.1177/1524838012454942

Referral to Health and Social Services for Intimate Partner Violence in Health Care Settings

2012· article· en· W2135959514 on OpenAlex
Maritt Kirst, Yu Janice Zhang, Aynsley Young, Alena Marshall, Patricia O’Campo, Farah Ahmad

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.

Bibliographic record

VenueTrauma Violence & Abuse · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsYork UniversityPublic Health OntarioOntario Tobacco Research UnitUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsReferralDomestic violenceMedicinePoison controlNursingQualitative researchHealth careSuicide preventionOccupational safety and healthFamily medicineMedical emergency

Abstract

fetched live from OpenAlex

Efficient and coordinated health care responses to intimate partner violence (IPV) are essential, given that health care settings are a major entry point for abused women who seek professional services. However, there is a lack of evidence on how IPV referrals are effectively made within health care settings. In order to help program planners and providers across sectors to address the complex and chronic issue of IPV, a greater understanding of the post-IPV identification referral process is essential. A scoping review of the evidence on IPV referral programs and processes in health care settings was undertaken to provide an overview of the state of evidence and identify pertinent gaps in existing research. The scoping review identified 13 evaluative studies and 6 qualitative, primarily nonevaluative studies that examined IPV referral programs and processes. Evaluative studies involved a variety of designs and IPV referral outcomes. Rich descriptions of barriers and facilitators to seeking referrals by victims and making referrals by health care providers emerged from the evaluative and qualitative studies, but were explored more in depth in the qualitative studies. This scoping review provides guidance on what is currently known about IPV referral programs in health care settings and provides a starting point for further research on effectiveness of referral processes.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.039
GPT teacher head0.374
Teacher spread0.335 · 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