Bibliographic record
Abstract
Abstract Are animals not ours to use? According to proponents of veganism such as Gary Francione, any and all use of animals by humans is exploitative and wrong. It is wrong because animals have intrinsic worth and humans' use of animals fails to respect that worth. Contra Francione, I argue that that there are conditions under which it may be morally appropriate to collect, consume, sell, or otherwise use animal products. Francione is mistaken in his belief that assigning intrinsic worth to a being is impossible if said being is also conceived as a resource. Using and (non‐instrumental) valuing are not mutually exclusive; if they were, many if not most human relationships would be deemed morally unacceptable. Through a series of thought experiments involving intra‐human relationships, I suggest that moral condemnation of relationships within which a less dependent party regularly takes from a more dependent party is indefensible. In fact, relationships of use between asymmetrically dependent parties are essential to the functioning of cooperative society, and are therefore desirable. My aims with this article are to convince readers of the need to reject principled veganism, and to garner support for new philosophical accounts of morally appropriate human‐nonhuman animal relationships.
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 | 0.025 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.086 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.011 |
| 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".