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Record W4377242482 · doi:10.1177/03085759231170879

Keeping in touch: Looked after children and young people’s views on their contact arrangements

2023· article· en· W4377242482 on OpenAlexaboutno aff
Julie Selwyn, Shirley Lewis

Bibliographic record

VenueAdoption & Fostering · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
Fundersnot available
KeywordsWelshPerspective (graphical)Quarter (Canadian coin)Ethnic groupAuditPsychologySocial contactKinshipNursingMedicineSocial psychologySociologyGeography

Abstract

fetched live from OpenAlex

Research reviews of the contact arrangements for children in care have highlighted gaps in evidence. Using data from 9,316 looked after children in England and Wales aged four to 18 years, the analysis aimed to gain an understanding of children’s views of their contact arrangements. Data came from the Your Life, Your Care wellbeing surveys distributed by 42 English and Welsh local authorities between 2016 and 2020. The analysis confirmed some previous findings but challenged others. While previous UK research has emphasised that the quality of contact is more important than frequency, from the young people’s perspective frequency was equally important. Most children wanted more contact with specific individuals (and their pets) to understand why decisions had been made and wanted contact to be normalised and in the community at times to suit their and their family’s circumstances. Children in kinship placements more frequently had contact, but a quarter of the sample had no parental contact. Being in residential care, male and of an ethnic minority background were associated with dissatisfaction. Life satisfaction was not associated with whether parental contact was or was not occurring but was statistically associated with whether young people felt their contact arrangements were ‘Just right’. Recommendations for improving practice and a tool to help agencies audit their services have been developed.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.466

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 studies0.0000.000
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 head0.042
GPT teacher head0.293
Teacher spread0.251 · 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 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

Citations9
Published2023
Admission routes1
Has abstractyes

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