Zones of Consensus and Zones of Conflict: Questioning the "Common Morality" Presumption in Bioethics
Bibliographic record
Abstract
Many bioethicists assume that morality is in a state of wide reflective equilibrium. According to this model of moral deliberation, public policymaking can build upon a core common morality that is pretheoretical and provides a basis for practical reasoning. Proponents of the common morality approach to moral deliberation make three assumptions that deserve to be viewed with skepticism. First, they commonly assume that there is a universal, transhistorical common morality that can serve as a normative baseline for judging various actions and practices. Second, advocates of the common morality approach assume that the common morality is in a state of relatively stable, ordered, wide reflective equilibrium. Third, casuists, principlists, and other proponents of common morality approaches assume that the common morality can serve as a basis for the specification of particular policies and practical recommendations. These three claims fail to recognize the plural moral traditions that are found in multicultural, multiethnic, multifaith societies such as the United States and Canada. A more realistic recognition of multiple moral traditions in pluralist societies would be considerable more skeptical about the contributions that common morality approaches in bioethics can make to resolving contentious moral issues.
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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 | 0.074 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.017 | 0.138 |
| Scholarly communication | 0.023 | 0.044 |
| Open science | 0.006 | 0.030 |
| Research integrity | 0.016 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".