Evaluation of a court liaison and diversion service in London over a quarter of a century
Bibliographic record
Abstract
Introduction Oxleas NHS Foundation Trust has run a Court Diversion Service in South East London since 1991. It provides services for people within the earlier stages of the Criminal Justice System. Objectives This evaluation aims to combine data from across the 25-year period since the introduction of the diversion scheme. It seeks to provide a longitudinal picture to elucidate the impact of service changes during this time. Methods The evaluation uses data obtained from a variety of sources for four points in time: 2015/2016, 2011, 1999 and 1991. Data across domains was collated to allow longitudinal analysis. Results After the initial introduction of the scheme in 1991, the total mean time on remand was noted to drop from 67.1 days to 49.5 days (P < 0.001). There were 280 referrals over 18 months in 1991, 210 per year in 1999, 190 in 2011 and 174 between April 2015 and March 2016. Violent crimes increased from 29% in 1991 to 47% in 2011. The proportion with schizophrenia decreased from 31% in 1991 to 18% in 1999, before increasing again to 25% in 2011. The use of Section 37 hospital order disposal decreased from 15% in 1991 to just 4% in 2011. Conclusions The court diversion scheme has produced significant benefits since it was introduced in 1991, despite a rise in the proportion of violent alleged offences. Changes to the service have seen decreased use of hospital orders. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".