Bibliographic record
Abstract
There has been considerable debate in the UK in recent years about the propriety of using various forms of ‘involuntary out-patient treatment’ for some individuals with serious mental illness (Eastman, 1995; Dyre, 1998; Burns, 1999; Moncrieff & Smyth, 1999; Sugarman, 1999). While most jurisdictions in the US have statutes that support involuntary out-patient treatment (Torrey & Kaplan, 1995), its use remains controversial (Slobogin, 1994; Diamond, 1995; Torrey, 1997). Involuntary outpatient treatment was originally proposed as a solution to the ‘revolving door syndrome’ (Geller, 1996). It has also been recognised, however, that it may provide a solution to the clinical and ethical dilemmas of allowing individuals who are incapable of making treatment decisions to discontinue treatment, with predictable deterioration to the point where they may harm themselves or others (Geller, 1990). This paper provides a review of controlled studies that have examined whether involuntary treatment in the community is effective.
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.
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 | 0.026 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".