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Record W4283589642 · doi:10.1080/26408066.2022.2073796

Impact of Adverse Childhood Experiences in the Manifestation of Intimate Partner Violence Victimization and Perpetration among College Students: Gendered Perspective

2022· article· en· W4283589642 on OpenAlexaboutno aff
Mariam Fatehi, Y. Joon Choi, Hyunkag Cho, Soonok An, Ga-Young Choi, Seunghye Hong

Bibliographic record

VenueJournal of Evidence-Based Social Work · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsDomestic violencePsychologyOddsIntervention (counseling)Logistic regressionClinical psychologyPoison controlDepression (economics)Injury preventionSuicide preventionPsychiatryMedicineMedical emergencyInternal medicine

Abstract

fetched live from OpenAlex

Purpose This study examined the effect of five types of adverse childhood experiences (ACEs) on Intimate Partner Violence (IPV) perpetration and IPV victimization for male and female students (N = 3,682).Method The data came from seven universities in the U.S. and Canada using multivariate logistic regression models.Results For female students, peer victimization (PV), childhood maltreatment (CM), exposure to domestic violence (EDV), drug use, and depression were significantly associated with higher odds of IPV perpetration. For male students, IPV perpetration was significantly associated with PV, CM, other physical and sexual violence (PSV), and alcohol use. IPV victimization was significantly associated with CM, EDV, PSV, drug use, and depression for female students. For male students, CM, PSV, alcohol use, and depression were associated with higher odds of IPV victimization.Discussion Because gender-specificity exists in the transmission process of ACEs and other risk factors for IPV, developing gender-specific approaches to IPV prevention and intervention on college campuses is necessary.

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)0.003
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 score0.185
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.052
GPT teacher head0.378
Teacher spread0.326 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

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