Human rights in the postgenomic era: Challenges and opportunities arising with epigenetics
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
Over the past twenty-five years, international organizations have adopted human rights declarations in an attempt to address emerging ethical, legal and social concerns associated with genetic research and technologies. While these declarations point to important challenges and potential issues in genetics, the focus on genetics has been criticized for promoting the idea that there is something unique about our genes, and that therefore, they deserve special protections in our laws. It is also argued that this ‘genetic exceptionalism’ perspective has contributed to a reinvigoration of genetic essentialism and determinism. In this article, we add to this criticism by pointing out gaps and flaws in current gene-focused human rights declarations in light of recent developments in the field of epigenetics. First, we show that these documents do not provide guidance for a responsible governance of epigenetic data (e.g., privacy protection) and an ethical use of individual epigenetic information (e.g., nondiscrimination). This is particularly concerning given the interest recently demonstrated by insurance companies, forensic scientists and immigration agencies in using epigenetic clock technologies. Second, we argue that findings in epigenetics could contribute to the promotion of second- and third- generation human rights, i.e., respectively, economic, social and cultural rights, and solidarity rights. We conclude by calling for international bioethics and human rights organizations to pay greater attention to epigenetics and other postgenomic sciences in the coming years.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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