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Record W1998757698 · doi:10.1080/0886571x.2011.550172

Beyond Control: Staff Perceptions of Accountability for Children and Youth in Residential Group Care

2011· article· en· W1998757698 on OpenAlexaff
Kiaras Gharabaghi, Jack Phelan

Bibliographic record

VenueResidential Treatment for Children & Youth · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsMacEwan UniversityToronto Metropolitan University
Fundersnot available
KeywordsAccountabilityResidential careFocus groupPerceptionPsychologyQualitative researchIntuitionPublic relationsMental healthFoster careHealth careNursingApplied psychologySocial psychologySociologyMedicinePolitical sciencePsychotherapist

Abstract

fetched live from OpenAlex

This article explores the perceptions of residential staff teams regarding the concept of accountability for children and youth living in group care situations. Using a qualitative research approach, the authors held focus groups with residential staff teams in children's mental health and private group care facilities and then interviewed the supervisors separately in an effort to explore how these teams conceive of their responsibility to teach children and youth about accountability, as well as in order to determine the specific tools used and approaches taken for this purpose. The authors found that a strong reliance on control-based approaches persists and that, furthermore, very little conceptual or theoretical thinking informs team discussions or approaches to holding children and youth accountable for their actions. It is argued here that there is an urgent need to seriously engage with residential care providers about the lived experiences of children and youth under conditions. The use of control and vigilance around the enforcement of program expectations are rarely focused on the individual needs of the clients and typically reflect the intuition or “common sense” of residential staff teams instead.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.021
GPT teacher head0.284
Teacher spread0.263 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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