In anticipation of a future period of incapacity: The Dutch 'levenstestament' from a legal, empirical and comparative perspective
Bibliographic record
Abstract
With an ageing population, the number of people with dementia is expected to increase in the coming decades. Dementia can seriously impair a person’s ability to act and decide. In the Netherlands, adults can provide for such a future period of incapacity through a so-called levenstestament. A levenstestament can include the appointment of an attorney for financial, medical and/or personal matters, but also the adult’s wishes, preferences and instructions regarding these matters. Over the past decade, the levenstestament has become increasingly popular in the Netherlands. A major concern, however, is that the levenstestament becomes active at a time when adults will generally be increasingly unable to supervise the execution of the levenstestament and indicate whether they are satisfied with the actions of their attorney. This book provides a thorough analysis of the current regulation and application of the levenstestament based on legal-normative and empirical research. Based on comparative law research, recommendations have been formulated to improve the regulation of the levenstestament and address problems that arise in practice.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".