Bibliographic record
Abstract
Drs Karagianis, Hastings, and Gray disagree with our assessment of the evidence on the effectiveness of community treatment orders (CTOs). In our reviews of studies from Canada and abroad, we apply recognised principles of evidence-based medicine (EBM) to assess the quality of the research. We found some studies show therapeutic benefits for CTOs. These include studies commissioned by governments, often conducted by nonacademic consultancies and not subject to peer review, and a number of small-scale, uncontrolled studies. These are the kinds of studies conducted in Canada. They do not provide robust evidence for efficacy of CTOs, especially when few high-quality studies report positive outcomes, and all the randomized studies and the best nonrandomized ones find no evidence of therapeutic benefit.
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 | 0.267 | 0.661 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.013 | 0.010 |
| Research integrity | 0.013 | 0.021 |
| Insufficient payload (model declined to judge) | 0.006 | 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".