Bibliographic record
Abstract
Since the early 1990s many jurisdictions have recognised psychiatric advance directives. In Australia, reviews of mental health legislation have been completed in New South Wales and the Northern Territory, and are on foot in Western Australia, South Australia, Queensland, Tasmania, the ACT and Victoria. To date, only the ACT and Victorian reviews have seriously countenanced the legislative recognition of advance directives. In the current environment of review and debate about the proper balance between rights and risks in psychiatry, the structure of comparable international provisions and international clinical experience with psychiatric advance directives can usefully inform Australian developments. This article outlines the relevant law in Australia and the legislative approaches adopted in Scotland, England and Wales, New Zealand, Canada and the United States of America. It argues that effective law reform in Australia should attend to international precedent, but also be mindful of the deeper human rights principles represented by the psychiatric advance directive movement.
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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 | 0.030 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.058 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 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".