The Challenges of Extreme Moral Stress: Claudia Card's Contributions to the Formation of Nonideal Ethical Theory
Bibliographic record
Abstract
Abstract This essay argues that Claudia Card numbers among important contributors to nonideal ethical theory (NET), and it advocates for the worth of NET. Following philosophers including Lisa Tessman and Charles Mills, the essay contends that it is important for ethical theory, and for feminist purposes, to carry forward the interrelationship that Mills identifies between nonideal theory and feminist ethics. Card's ethical theorizing assists in understanding that interrelationship. Card's philosophical work includes basic elements of NET indicated by Tessman, Mills, and others, and further offers two important and neglected elements to other nonideal ethical theorists: (i) her rejection of the “administrative point of view,” and (ii) her focus on “intolerable harms” as forms of “extreme moral stress” and obstacles to excellent ethical lives. The essay concludes that Card's insights are helpful to philosophers in developing nonideal ethical theory as a distinctive contribution to, and as a subset of, nonideal theory.
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.
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 | 0.021 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.096 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.012 |
| 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".