Community treatment orders: the ethical balancing act in community mental health
Bibliographic record
Abstract
Community treatment orders (CTOs) are legal mechanisms by which an individual with a mental illness and a history of non-compliance and potential for violence can be mandated (against their will) to undergo psychiatric treatment in an outpatient setting. Although CTOs are increasingly being adopted by governments as a means of protecting both mentally ill persons and society itself, their use continues to stimulate considerable debate. While there is some evidence of their potential benefits in promoting treatment compliance and reducing hospital stays, there is concern that they infringe on the mental health client's human rights and freedoms. Consideration of the ethical and practical implications of the use of CTOs must continue. In this paper, some of the most pressing issues are identified and discussed.
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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 | 0.046 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.053 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.030 | 0.019 |
| Insufficient payload (model declined to judge) | 0.003 | 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".