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Research Review: In a rush to permanency: preventing adoption disruption

2007· article· en· W2029502895 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueChild & Family Social Work · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
Fundersnot available
KeywordsFoster careVariety (cybernetics)Family preservationFamily reunificationWelfareIdeal (ethics)PsychologyPublic relationsMedicinePolitical scienceCriminologyNursingLawComputer science

Abstract

fetched live from OpenAlex

ABSTRACT Since the late 1990s, US, UK and Canadian policy have increasingly focused on improving permanency outcomes for looked‐after children. Although the ideal permanency outcome of reunification is attained for about half of the children entering out‐of‐home care, an increasing number of children are adopted each year. The vast majority of adoptions are stable and secure, but concerns about adoption disruption haunt child welfare workers when making this important permanency decision. Despite a variety of definitions employed in the literature, adoption disruption is a general term used to describe the failure or breakdown of an adoptive child’s placement. Studies dating back to the 1970s have reported adoption disruption rates and the characteristics associated with those involved in such cases. This paper reviews available research, principally from the United States, and offers possible explanations for the wide range of reported disruption rates in the literature. After reviewing the research, practice implications for improving adoption outcomes and suggestions for future research are presented.

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.

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)0.007
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
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 head0.061
GPT teacher head0.395
Teacher spread0.333 · 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