The ‘serious’ factor in germline modification
Bibliographic record
Abstract
Current advances in assisted reproductive technologies aim to promote the health and well-being of future children. They offer the possibility to select embryos with the greatest potential of being born healthy (eg, preimplantation genetic testing) and may someday correct faulty genes responsible for heritable diseases in the embryo (eg, human germline genome modification (HGGM)). Most laws and policy statements surrounding HGGM refer to the notion of 'serious' as a core criterion in determining what genetic diseases should be targeted by these technologies. Yet, this notion remains vague and poorly defined, rendering its application challenging and decision making subjective and arbitrary. By way of background, we begin by briefly presenting two conceptual approaches to 'health' and 'disease': objectivism (ie, based on biological facts) and constructivism (ie, based on human values). The basic challenge under both is sorting out whether and to what extent social and environmental factors have a role in helping to define what qualifies as a 'serious' disease beyond the medical criteria. We then focus on how a human rights framework (eg, right to science and right to the highest attainable health) could integrate the concepts of objectivism and constructivism so as to provide guidance for a more actionable consideration of 'serious'. Ultimately, it could be argued that a human rights framework, by way of its legally binding nature and its globally accepted norms and values, provides a more universal foundation for discussions of the ethical, legal and social implications of emerging or disruptive technologies.
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How this classification was reachedexpand
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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.009 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".