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Record W2807610533 · doi:10.18357/ijcyfs92201818212

ACKNOWLEDGING THE COMPLEXITY OF PROCESSES LEADING TO FOSTER CARE BREAKDOWN

2018· article· en· W2807610533 on OpenAlexvenueno aff
Clara Bombach, Thomas Gabriel, Renate Stohler

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
Fundersnot available
KeywordsTerminologyPerspective (graphical)AmbiguityFoster careQuality (philosophy)Process (computing)PsychologyMedicineComputer scienceNursingEpistemology

Abstract

fetched live from OpenAlex

Family-based solutions for children in care are the preferred option in European countries on the grounds of both cost and quality. Yet, too often, foster care placements intended to be long term are terminated unexpectedly early. Few studies have identified factors leading to unexpected breakdown and fewer still have translated such findings into practical guidance for professionals. This article outlines: (a) the ambiguity and contradictions in the use of terminology (e.g., instability, breakdown, disruption) in several international studies; (b) the adoption of a one-sided, file-based, systemic perspective in recent studies of foster care instability, breakdown, and disruption; and (c) empirical data collected from interviews with foster children. Foster care breakdown is shown to be a process that takes place on several levels. In addition to the actual breakdown event, the situation of the child before the placement, the situation during the placement, the emergence and development of the crisis and the consequences of the breakdown for all those involved are all part of the process. It is only in retrospect that the ending of a foster care process is perceived as a breakdown. Assessments of whether it was planned or unplanned, expected or unexpected, and desirable or undesirable are meaningful only from an individual perspective. Such a perspective must be clearly identified: different people experience and remember the same breakdown in different ways, and its significance for their personal biographies may vary.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.269

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 studies0.0000.001
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 head0.084
GPT teacher head0.360
Teacher spread0.276 · 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 designQualitative
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

Citations9
Published2018
Admission routes1
Has abstractyes

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