Keeping in touch: Looked after children and young people’s views on their contact arrangements
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".