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Record W1985930479 · doi:10.1177/1557085113490782

Victim Experiences and Perspectives on Police Responses to Verbal Violence in Domestic Settings

2013· article· en· W1985930479 on OpenAlexafffund
Catherine Stewart, Debra Langan, Stacey Hannem

Bibliographic record

VenueFeminist Criminology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsWilfrid Laurier University
FundersWilfrid Laurier University
KeywordsSeriousnessVerbal abusePsychologyPerceptionSocial psychologyQualitative researchCriminologyDomestic violenceHuman factors and ergonomicsPoison controlSuicide preventionPolitical scienceSociologyMedicineMedical emergencyLaw

Abstract

fetched live from OpenAlex

This interdisciplinary, qualitative study explores why individuals called the police in noncriminal, verbally aggressive situations and how they perceived police responses. In-depth interviews were conducted with 30 individuals, mostly women. While some reported positive perceptions of the police response, the participants’ accounts underscored the seriousness of verbal violence and revealed that when women seek help from police they often perceive the resulting response as inadequate and/or unfair. This study highlights the importance of recognizing that verbal violence is often part of a “fabric of abuse” that may include criminal behavior and considers implications for police practice.

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)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0140.013
Scholarly communication0.0080.006
Open science0.0020.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.053
GPT teacher head0.354
Teacher spread0.301 · 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 designQualitative
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

Citations36
Published2013
Admission routes2
Has abstractyes

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