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Record W2183287086 · doi:10.22329/csw.v14i2.5879

A Critical Analysis of the use of Attachment Theory in Cases of Domestic Violence

2019· article· en· W2183287086 on OpenAlexvenueno aff
Fiona Buchanan

Bibliographic record

VenueCritical Social Work · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsDomestic violencePositivismAffect (linguistics)Critical theoryPerspective (graphical)SociologyAttachment theoryCriminologyPower (physics)Social psychologyPoison controlPolitical sciencePsychologySuicide preventionLawMedicine

Abstract

fetched live from OpenAlex

Social policies and social work practices are increasingly influenced by attachment theory. Women who have been subjected to domestic violence by male partners are being assessed within this discourse, which takes little account of societal perspectives, which sustain injustices and power differentials. Domestic violence is known to be a major social problem but when attachment theory is applied to women and their babies in domestic violence it negates knowledge based in lived experiences. Rather attachment theory is informed by non-gendered family violence perspectives and research instruments, which frame domestic violence within an individualised perspective. In this way, women and their babies are observed and classified without regard for the societal factors, which affect them. In view of this, there is a need for critical social workers to question attachment theory and the positivist research instruments, which are being used to inform theory and practice. Particularly with regard to domestic violence as a gendered, societal issue, a broad perspective, which promotes a social justice view and the need for social change is indispensable.

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)0.017
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.003
Science and technology studies0.0120.020
Scholarly communication0.0060.006
Open science0.0020.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.398
Teacher spread0.344 · 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 designTheoretical or conceptual
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

Citations16
Published2019
Admission routes1
Has abstractyes

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