Moral presentation of genetics-based narratives for public understanding of genetic science and its implications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The increasing number of sequenced genes that can be used to develop tests for inherited conditions has stimulated an increasing number of genetics-based narratives by journalists, novelists, playwrights, filmmakers, and health-care educators. Genetics-based narratives are to be welcomed if the public is to understand genetic science and its implications on persons, families, and communities. However, a number of important ethical issues insist caution in their research and presentation. Just as the requirements for informed consent to undergo genetic testing exceed the requirements for informed consent to undergo other types of medical testing because of the inherent complex relationships (such as between parent and child, gene carrier and other family members, gene carrier and ethnic community) and because of concerns regarding privacy and insurance discrimination, the requirements for informed consent to present a genetics-based narrative must exceed the requirements for informed consent to present other medical narratives. We recommend that a transmedia, multidisciplinary, international conference should be convened to develop guidelines for the moral presentation of genetics-based narratives, whose deliberations should be informed by the protections provided for narrative research participants, the requirements of consent for genetic testing (which include a counseling process involving all appropriate family members), and a professional obligation to do no harm to the persons and families whose genetics-based stories we present.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it