Exploring knowledge of neurodisabilities and access to education in custody at a youth correctional centre in Cape Town, South Africa
Bibliographic record
Abstract
Youth and young adults in conflict with the law (YCWL) in custody have needs across different areas, such as education, health, social, and emotional domains. Amongst other efforts, rehabilitation approaches in prisons often include vocational training and education. The latter is especially important for those in prison, who are still minors. Research that focuses on education for young people in custody is therefore emerging. The study aimed to explore access to education in custody, educational needs, and awareness of neurodisabilities using semi-structured interviews with relevant stakeholders (N = 9) at a correctional centre. Thematic analysis, using an inductive approach, was used to analyze the data. In keeping with previous studies, prison stakeholders reported that they are not qualified nor trained to deal with YCWL with neurodisabilities and that they are not “experts”. Although there is a provision of education in custody for YCWL, several factors impact their access to education in custody, including koffender factors (high-risk offenders, disruptive offenders displaying problematic behaviours, and the presence of neurodisabilities) and systemic factors (prison overpopulation and a lack of educators). The results of this study may be used to inform policy implementation in terms of rehabilitation and the use of proper screening and assessment tools to screen for various neurodisabilities in South African YCWL population, as well as providing training and support for prison stakeholders, to work effectively with YCWL who may present with neurodisabilities. Additionally, the schooling structures in youth correctional centres may be reformed, to better accommodate for educational needs of YCWL, including those with neurodisabilities.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".