The sequencing of interventions with offenders: views of offender managers and supervisors
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the views and opinions of offender supervisors and offender managers regarding the sequencing of interventions for prisoners in England. More specifically, the research aims to gain an understanding of any barriers to implementing desired practice. Design/methodology/approach Semi-structured interviews were conducted with ten participants located across four HM prisons in the West Midlands. Questions were designed to gather information and views regarding: current practice in the area of sequencing of interventions; opinions on the potential importance of coherent sequencing of interventions; views on how interventions should be sequenced; and what, if any, issues impacted upon coherent sequencing. Thematic analysis was used to identify, analyse and report themes within the interviews. Findings Participants discussed current practice regarding the sequencing of interventions and made suggestions regarding tailoring the sequence of interventions to the individual offender. The issue of readiness to change was emphasised (i.e. engagement with interventions will increase where offenders are able to participate in an intervention when they feel ready to do so). In addition, participants commented that they felt there to be insufficient resources at their disposal which led to barriers to the coherent sequencing of interventions (e.g. waiting lists for treatment programmes). Practical implications Suggestions were made by participants regarding the coherent sequencing of interventions; for example, providing prisoners with experience of a generic group intervention prior to an offence-specific intervention, prioritising motivation to change and being responsive to the needs of individual offenders. Originality/value The study provides insight regarding the sequencing of interventions from the perspective of offender supervisors and offender managers who are involved in the planning of treatment programmes across the course of an offender’s sentence.
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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 | 0.049 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".