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Record W4389267534 · doi:10.47772/ijriss.2023.7011033

Male Police involved Intimate Partner Violence: Is it more Dangerous than Abuse by Civilians? An Argumentative Analysis

2023· article· en· W4389267534 on OpenAlexaboutno aff
Naila Sohrat Tasbiha

Bibliographic record

VenueInternational Journal of Research and Innovation in Social Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerCriminologyScrutinyPolice brutalityDomestic violencePower (physics)Hegemonic masculinityUse of forceArgument (complex analysis)PsychologyPolitical scienceMasculinitySocial psychologyLawPoison controlSuicide preventionMedicineMedical emergency

Abstract

fetched live from OpenAlex

In the wake of the killing of George Floyd, Canadian and US policing has received mass scrutiny. These violent police behavior is currently prompting questions about the appropriate use of force by police officers. Police use of force usually focuses on police officer’s brutality in their official capacity, but there is a lack of empirical data on brutality and abuse perpetrated by police against their intimate partners in their private family lives. Although police officers are more likely than civilians to abuse their partners, the power and training provided to police officers by the state make them significantly more dangerous as domestic violence perpetrators. “Feminist theory” and “Hegemonic Masculinity theory” have been applied to understand the power and control that police officers have due to their training, which causes them to be considered more violent and dangerous for their families, especially for their intimate partners. To support the argument, three key themes have emerged: police abusers are skilled abusers; victims face a tremendous struggle to report the abuse; and available support systems for the victims of police abusers sometimes not adequate for them. Finally, some policy implications have been provided to address this problematic and potentially more dangerous issue.

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 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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.014
Science and technology studies0.0010.002
Scholarly communication0.0000.002
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 head0.109
GPT teacher head0.502
Teacher spread0.393 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Research and Innovation in Social ScienceSame topicIntimate Partner and Family ViolenceFrench-language works237,207