Communication of genetic information in the palliative care context: Ethical and legal issues
Bibliographic record
Abstract
As scientific understanding of the heritable aspects of cancer deepens, the need to effectively communicate genetic information within the families of cancer patients becomes more acute. In the palliative care context, the question of when and how to disclose a patient’s genetic information raises a host of ethical, legal, and social issues, including the challenges of communicating during the end-of-life stage and complex familial and cultural dynamics. In this paper, the authors outline the legal components of these issues in three civil law jurisdictions with similarly comprehensive approaches to healthcare and palliative care - Quebec, Belgium, and France - and provide insights from bioethics literature and normative documents on the disclosure of genetic information at the end of life. From this research, the authors propose a strategy for palliative care providers who are considering available options to communicate hereditary health information.
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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 | 0.039 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.048 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.013 | 0.010 |
| 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".