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Record W2045103829 · doi:10.1093/bjsw/bcs039

Social Workers' Use of Power in Relationships with Grandparents in Child Welfare Settings

2012· article· en· W2045103829 on OpenAlexaff
James Gladstone, Katharine Fitzgerald, Ralph Adams Brown

Bibliographic record

VenueThe British Journal of Social Work · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGrandparentNegotiationReciprocity (cultural anthropology)KinshipAgency (philosophy)DirectiveFoster parentsWelfarePower (physics)PsychologySocial psychologySocial workDevelopmental psychologySociologyPolitical scienceFoster careEconomic growthMedicineNursingEconomicsSocial science

Abstract

fetched live from OpenAlex

This paper focuses on ways in which social workers use power in their relationships with grandparents who are caring for grandchildren involved with child welfare agencies. Also examined are the ways in which grandparents perceive this use of power. Qualitative data were gathered from forty-three social workers and thirty-two grandparents in kinship care settings. Findings showed that social workers' expression of power falls into three main categories. Workers ‘dispense resources’, which include the provision of material support and services, the use of clinical skills and their influence over the middle generation. Workers can be ‘directive’, which involves their controlling interaction and defining the meanings of help. They also ‘manage negotiations’, which can occur in both an open and an implicit manner. Findings showed that workers' use of power can be beneficial to grandparents. A central issue for grandparents is whether there is reciprocity in their relationships with workers. Our conclusion is that being less directive and engaging in negotiations will result in collaborative relationships in which the needs of grandparents, as well as the agency, are more likely to be met.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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.

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
Published2012
Admission routes1
Has abstractyes

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