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Record W4306749522 · doi:10.4324/9781003319368

Children's Rights to Participate in Out-of-Home Care

2022· book· en· W4306749522 on OpenAlexaboutno aff
Claudia Equit, Jade Purtell

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHistoryPsychology

Abstract

fetched live from OpenAlex

For centuries, residential child and youth care systems worldwide have provided homes for vulnerable children and adolescents. The implementation of children's rights, especially the right of participation, is assessed as an important base for promoting the best interests of the child in an out-of-home care environment. Featuring contributions from distinguished international authors, this volume offers an in-depth understanding of crucial participation processes and underlying power structures when involving young people in decision-making about their care and everyday life in different out-of-home care institutions. Contributions cover a broad spectrum of current research findings concerning the participation of young people in foster families and residential living groups in Australia, Canada, Germany, Ireland, Italy, Portugal, Norway, Sweden, and Switzerland as well as cross-nationals perspective on children and young people's participation in foster and residential care placements in Great Britain and France. The volume fills major gaps concerning the participation of young people in different out-of-home care and policy settings and will be required reading for policymakers, researchers, practitioners, scholars, and students interested in increasing opportunities for young people's participation and creating better out-of-home care settings for vulnerable young people.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.004

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 head0.033
GPT teacher head0.321
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations8
Published2022
Admission routes1
Has abstractyes

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