Bibliographic record
Abstract
The use of an advance directive, when drafted in accordance with the MCA, allows a person the right to refuse specified treatment at a later stage of their life, should they become incapacitated. This means that they, rather than others, can determine what would be in their own best interest. However, even when a person has made an advance directive, their express wishes can be overruled by the court if they have acted in such a way, or there has been a change in circumstances, that is inconsistent with their advance directive. That is, in the event of clear inconsistencies with an advance directive, the court will rule in favour of the preservation of life. Thus, in certain circumstances, it may be justifiable for an advance directive not to be binding. This review aims to evaluate the practices around advance healthcare directives in England and Wales. In particular, it focuses on advance directives for refusal of life-sustaining treatment, and how the courts interpret Section 25(2) (c) MCA in determining when an advance directive is no longer valid or applicable to the specified treatment as a result of inconsistencies subsequent to the document’s drafting. Furthermore, it contends that a mandatory capacity assessment prior to drafting an advance directive could eliminate contentious issues at a later stage.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".