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Record W2281820459 · doi:10.1177/0886260516632812

I Am Not in Your Shoes: Low Perspective Taking Mediating the Relation Among Attachment Insecurities and Physical Intimate Partner Violence in Chilean University Students

2016· article· en· W2281820459 on OpenAlexaff
Marie‐France Lafontaine, Mónica Guzmán‐González, Katherine Péloquin, Christine Lévesque

Bibliographic record

VenueJournal of Interpersonal Violence · 2016
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversité de MontréalUniversity of Ottawa
Fundersnot available
KeywordsPerspective (graphical)Domestic violencePsychologyAnxietyRomanceAssociation (psychology)Social psychologyPoison controlAttachment theoryDevelopmental psychologySuicide preventionHuman factors and ergonomicsInjury preventionStructural equation modelingClinical psychologyMedicineMedical emergencyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Guided by the attachment theory, this study tested the degree to which perspective taking mediates the effects of romantic attachment on the use of physical intimate partner violence (IPV) toward the partner. Participants consisted of 608 Chilean university students involved in a romantic relationship, among whom 44.2% of women and 34.7% of men reported inflicting at least one act of violence toward their partner during the previous year. Results from a structural equation model showed that the association between avoidance of intimacy and physical IPV is mediated by perspective taking for both men and women. However, perspective taking mediated the link between attachment anxiety and physical IPV in women only. Our findings underline the importance of the individual's sense of attachment security in relation to their ability to empathize with their partners, as well as prevent the perpetration of physical IPV against them.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.367
Teacher spread0.347 · 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 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

Citations18
Published2016
Admission routes1
Has abstractyes

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