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Record W2143817089 · doi:10.1177/0192513x07306980

Love as a Battlefield

2007· article· en· W2143817089 on OpenAlexaff
Colleen J. Allison, Kim Bartholomew, Ofra Mayseless, Donald G. Dutton

Bibliographic record

VenueJournal of Family Issues · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsDistancingPsychologyThematic analysisSocial psychologyContext (archaeology)BattlefieldDomestic violenceAttachment theoryAbusive relationshipDevelopmental psychologyPoison controlQualitative researchHuman factors and ergonomicsCoronavirus disease 2019 (COVID-19)SociologyMedicine

Abstract

fetched live from OpenAlex

The authors explored the attachment dynamics of heterosexual couples identified for male partner violence. Based on semistructured interviews, participants were assessed for attachment orientations. Based on a thematic analysis of the interviews, two strategies for regulating distance within these relationships were identified: pursuit and distancing. Partners' abusive acts often appeared to serve one of these attachment strategies. As a pursuit strategy, violence forced one partner to focus on the other, and as a distancing strategy, violence served to push a partner back when the perpetrator had been approached too closely and perceived no other means of escape or self-protection. To understand the context in which individuals acted abusively, the authors considered the interaction between the attachment orientations of both partners as they sought to regulate their emotional and physical proximity. Findings highlight the relational basis of intimate 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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.005
Scholarly communication0.0050.005
Open science0.0000.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.042
GPT teacher head0.401
Teacher spread0.359 · 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

Citations160
Published2007
Admission routes1
Has abstractyes

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