Risk and need assessment in British probation: the contribution of LSI-R
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract From 1996 until about 2000 the Canadian Level of Service Inventory – Revised (LSI-R) was in use in a number of probation services in England and Wales, and it is still in use in the Jersey Probation and After-Care Service. This article reviews what has been learned about risk and need assessment in British probation through the use of LSI-R, drawing on data collected for a Home Office study and for evaluative research in Jersey. Particular areas of interest are accuracy, differences between male and female offenders, the comparative effectiveness of probation and community service, the apparent counterproductive impact of probation on low-risk offenders, and the efficacy of risk-related change measurement. The conclusion points out the wide-ranging advantages of risk/need assessment for probation services, and discusses why services in England and Wales have been slow to benefit from this.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it