Genetic Information Access, a Legal Perspective: A Duty to Know or a Right Not to Know, and a Duty or Option to Warn?
Bibliographic record
Abstract
Abstract It is often argued that concern with basic personal privacy suggests that individuals should be allowed to decide in isolation whether to obtain genetic information through testing and whether to make the results available to others. However, the familial nature of genetic information complicates matters by raising question regarding whether an individual has a moral duty to discover and/or reveal existing genetic information to possibly affected family members. Alternatively, if this information would harm family members, do individuals have a duty not to obtain, or at least not to divulge, genetic test results? What role, if any, should legislation play in dealing with access to genetic information at the familial level? Do health care professionals have a responsibility or a right to inform close family members of the genetic status of a related individual? We consider the personal, familial and public health care perspectives regarding this debate.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.050 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.020 | 0.014 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".