The Role of the Medical Expert in the Retrospective Assessment of Testamentary Capacity
Bibliographic record
Abstract
Objectives: Physicians and other mental health experts are increasingly called on to assist the courts with the determination of testamentary capacity. We aim to improve the understanding of the retrospective assessment of testamentary capacity for medical experts in order to provide more useful reports for the court’s determinations and to provide a methodology for the retrospective assessment of testamentary capacity. Method: Medical experts with experience in the retrospective assessment of testamentary capacity collaborated with lawyers who practice estate litigation. The medical literature on the assessment of testamentary capacity was reviewed and integrated. The medical experts provided a clinical perspective, while the lawyers ensured that the case law and legal perspective were integrated into this review. Results: The focus and limitations of the medical expert are outlined including the need to be objective, nonpartisan, and fair. For the benefit of the court, the medical expert should describe the nature and severity of relevant medical, psychiatric, and cognitive disorders, and how they may impact on the specific criteria for testamentary capacity as defined by the leading case of Banks v Goodfellow. Medical experts should opine only on the issue of vulnerability to influence and defer to the court to determine the facts of the case regarding any influence that may have been exerted. Conclusions: Although the ultimate determination of testamentary capacity is a legal one, medical experts can help the court achieve the most informed legal decision by providing relevant information on clinical issues that may impact the criteria for testamentary capacity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".