Bibliographic record
Abstract
According to a widely shared intuition, normal adult humans require greater moral concern than normal, adult animals in at least some circumstances. Even the most steadfast defenders of animals' moral status attempt to accommodate this intuition, often by holding that humans' higher-level capacities (intellect, linguistic ability, and so on) give rise to a greater number of interests, and thus the likelihood of greater satisfaction, thereby making their lives more valuable. However, the moves from capacities to interests, and from interests to the likelihood of satisfaction, have up to now gone unexamined and undefended. I argue that context plays a morally significant role both in the formation of an individual's capacities, and in the determination of the individual's interests and potential for satisfaction based on those capacities. Claims about an individual's capacities and interests are typically presented as unconditional; but on closer examination, they are revealed to be contingent on tacit assumptions about context. Until we develop an understanding of how to account for the role of context within our moral theories, attempts to defend special moral concern for human beings based on their superior capacities are less firmly grounded than is commonly thought.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".