‘Listen to us’ - Exploring the perceptions of young people on the impact of custody
Bibliographic record
Abstract
Persistent attention on children and young people in the United Kingdom has been characterised by the growing anxiety of threatening and rebellious young people, termed by Pearson (1983) as ‘respectable fears’. This growing anxiety has resulted in expansion of the youth justice system, with emphasis on developing effective and sustainable youth offending interventions to reduce recidivism and enhance outcomes for young people (Nevill and Lumley, 2011). The process for developing effective and sustainable custodial interventions rely on output and outcome data, with limited importance placed on understanding the wider impact (e.g. education, relationships, non-cognitive skills etc.). Using an adapted sequential research design, the researcher adopted a mixed methodological approach fuelled by a desire to facilitate the active participation of young people in custody. This conference presentation disseminates findings from the semi-structured interviews conducted with young people in custody. To ensure children and young people have a voice in the youth justice process, the researcher seeks to demonstrate how the perceptions of young people on impact can be useful for organisations engaged in youth justice interventions. This paper makes an original contribution to knowledge through the identification of suitable data collection methods for identifying the wider impact of custody, specifically in Secure Training Centres.
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 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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".