Bibliographic record
Abstract
I worked at Ashworth between 1991 and 1995 as a nurse therapist in a centrally located rehabilitation unit. There were two of these rehabilitation centres, situated in the North and South sites of the hospital campus, reflecting the previous configuration of services in two separate hospitals (see Chapter 1). The South Rehabilitation Centre was one of the few aspects of Ashworth that attracted positive comments in the Blom-Cooper Inquiry: ‘Dr Sines and Mr Thompson singled out the environment of the rehabilitation department for praise, a well designed oasis of purposeful activity in a desert of bleak wards’ (Blom-Cooper et al., 1992, p.146). The centre operated somewhat along the lines of a ‘day hospital’ within the hospital, with patients travelling from the wards to attend for specific groups or one-to-one psychotherapies. It was managed and staffed by a small team of nurses, who worked alongside other colleagues to plan and deliver interventions, often co-working in pairs to facilitate groups. There was a strong emphasis upon behavioural and cognitive-behavioural approaches informed by the work of Robert Ross and colleagues (Ross and Gendreau, 1980; Ross and Fabiano, 1985) in the Canadian correctional system and the developing UK evidence base for ‘what works’ in offender therapy (McGuire, 1995). Indeed, the clinical psychologist James McGuire, one of the leading lights in this field, worked in Ashworth at the time and made a significant contribution to the work of the centre. Following the Blom-Cooper Inquiry, there was an impetus to develop an additional rehabilitation centre located in the North site of the hospital, and it was here that I was recruited to work. Another member of the new team staffing the North centre was Ged McCann, who already had an extensive career within Ashworth and brought with him an interest in psychosocial approaches and a commitment to better meeting the needs of relatives of people detained in secure hospitals. Building upon previous work in the hospital, Ged inspired and instigated further efforts that were eventually to lead to the proposals which are the subject of this chapter.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.041 | 0.022 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.018 | 0.042 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".