Bibliographic record
Abstract
Over the past decade, epigenetic studies have been providing further evidence of the molecular interplay between gene expression and its health outcomes on one hand, and the physical and social environments in which individuals are conceived, born and live on the other. As knowledge of epigenetic programming expands, a growing body of literature in social sciences and humanities is exploring the implications of this new field of study for contemporary societies. Epigenetics has been mobilised to support political claims, for instance, with regard to collective obligations to address socio-environmental determinants of health. The idea of a moral 'epigenetic responsibility' has been proposed, meaning that individuals and/or governments should be accountable for the epigenetic programming of children and/or citizens. However, these discussions have largely overlooked important biological nuances and ambiguities inherent in the field of epigenetics. In this paper, we argue that the identification and assignment of moral epigenetic responsibilities should reflect the rich diversity and complexity of epigenetic mechanisms, and not rely solely on a gross comparison between epigenetics and genetics. More specifically, we explore how further investigation of the ambiguous notions of epigenetic normality and epigenetic plasticity should play a role in shaping this emerging 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 | 0.028 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.080 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".