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Record W4377043525 · doi:10.1111/cfs.13029

The potential role of social and familial networks in shaping the well‐being of children in shelters for women survivors of intimate partner violence

2023· article· en· W4377043525 on OpenAlexaff
Anat Vass, Muhammad M. Haj‐Yahia

Bibliographic record

VenueChild & Family Social Work · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsMcGill University
FundersHaruv Institute
KeywordsDisconnectionGrandparentThematic analysisWorryDevelopmental psychologyPsychologyIntervention (counseling)Qualitative researchDomestic violenceNeighbourhood (mathematics)Social psychologySuicide preventionPoison controlSociologyMedicinePsychiatryEnvironmental healthPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Abstract Children living in households where severe intimate partner violence (IPV) exists sometimes move with their mothers to shelters for battered women. Although there is an increased interest in research exploring children's exposure to IPV, little is known about children's subjective experiences during their stay in shelters. The present study examines children's views of their disconnection from their social and familial networks during their stay in a shelter. Using qualitative methods, 32 children, ages 7–12 years, who resided in a shelter were interviewed. Thematic analysis was implemented to develop codes and themes. The following five themes emerged from the data analysis: (a) absence of grandparents, (b) worry about older siblings, (c) disconnection from the neighbourhood, (d) missing their house and (e) disconnection from previous school and classmates. Findings suggest that children's disconnection from previous formal and informal networks significantly affected their well‐being. The findings are discussed and interpreted in light of selected key concepts of Bronfenbrenner's bioecological model. The limitations of this study are discussed, along with implications for future research, as well as highlights for future intervention.

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 score0.491
Threshold uncertainty score0.928

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.279
Teacher spread0.265 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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