Bibliographic record
Abstract
Bioethicists criticize Jürgen Habermas’s argument against “liberal eugenics” for many reasons. This essay examines one particular critique, according to which Habermas misunderstands the implications of human evolution. In adopting Hannah Arendt’s concept of “natality,” Habermas seems to fear that genetically modified children will lose the contingency of their births, which would impair their capacity for political action; but according to evolutionary theory, bioethicists argue, this fear is unfounded. I explore this objection by entertaining the hypothesis that Habermas’s argument assumes Arendt’s interpretation of Darwinian evolution in addition to her conception of natality, and then I answer it by contrasting the conceptions of evolution held by Habermas, by Arendt, and by Habermas’s critics. Les bioéthiciens critiquent l’argument de Jürgen Habermas contre « l’eugénisme libéral » pour de nombreuses raisons. Cet essai examine une critique en particulier, selon laquelle Habermas comprend mal les implications de l’évolution humaine : en adoptant le concept de la « natalité » de Hannah Arendt, Habermas semble craindre que les enfants soumis à une modification génétique ne perdent la contingence propre à leur naissance, une perte qui diminuerait leur capacité pour l’action politique, mais selon la théorie de l’évolution, les bioéthiciens soutiennent que cette peur est sans fondement. J’explore cette objection à Habermas en considérant l’hypothèse que, en plus du concept de la natalité, Habermas suppose aussi l’interprétation arendtienne de l’évolution biologique de Darwin, et j’y répond en confrontant cette conception de l’évolution avec la conception propre à Habermas et avec celle des bioéthiciens qui lui ont répondu.
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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 | 0.046 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.067 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.055 | 0.059 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".