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Record W2138932099 · doi:10.1017/s0954579411000678

Mothers' physical abusiveness in a context of violence: Effects on the mother–child relationship

2012· article· en· W2138932099 on OpenAlexaboutno aff
Susan G. Timmer, Dianne Thompson, Michelle A. Culver, Anthony J. Urquiza, Shannon Altenhofen

Bibliographic record

VenueDevelopment and Psychopathology · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyDomestic violenceContext (archaeology)Physical abuseDevelopmental psychologyPoison controlInjury preventionChild abuseHuman factors and ergonomicsSuicide preventionQuarter (Canadian coin)Clinical psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the effects of mothers' physical abusiveness on the quality of the mother-child relationship, and note how it further varied by their exposure to interparental violence (IPV). The sample consisted of 232 clinic-referred children, aged 2 to 7 years, and their biological mothers. Slightly more than a quarter of the children (N = 63, 27.2%) had been physically abused by their mothers; approximately half of these children also had a history of exposure to IPV (N = 34, 54%). Investigating effects of physical abuse in the context of IPV history on mothers' and children's emotional availability, we found that physically abused children with no IPV exposure appeared less optimally emotionally available than physically abused children with an IPV exposure. However, subsequent analyses showed that although dyads with dual-violence exposure showed emotional availability levels similar those of nonabusive dyads, they were more overresponsive and overinvolving, a kind of caregiving controllingness charasteric of children with disorganized attachment styles. These findings lend some support to the notion that the effects of abuse on the parent-child relationship are influenced by the context of family violence, although the effects appear to be complex.

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 score0.477
Threshold uncertainty score0.234

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 integrity0.0000.000
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 head0.025
GPT teacher head0.319
Teacher spread0.294 · 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

Citations15
Published2012
Admission routes1
Has abstractyes

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