Bibliographic record
Abstract
A challenge has come knocking at the doors of courts and governments worldwide: more and more animal rights scholars and activists are demanding that other animals have fundamental rights akin to those humans already possess. In his book, Fasel's task is to answer the ‘most urgent question’ this gives rise to: ‘can animals be granted fundamental rights without putting human rights in jeopardy?’ (p. 4). This question produces profound disagreement, and the book provides a useful, and comprehensive map of its contours (chaps. 2–4). Fasel argues that most, if not all, accounts of human and animal rights sit somewhere on the spectrum between two opposing ideal-types: ‘Aristocratic’ accounts (chap. 3) and ‘Meritocratic’ accounts (chap. 4). Aristocratic accounts prioritize coherence with two principles: that humans are one another's equals (pp. 58–59) and that we are morally ‘special’ and ‘separate’ from other animals (pp. 59–60). In contrast, Meritocratic accounts base rights on purely natural properties (pp. 78–81), such as sentience. A range of contemporary views fall under the Aristocratic umbrella, including those of Jeremy Waldron and Anne Phillips. Similarly, a range of views are Meritocratic in nature, including the increasingly popular sentientist rights approach defended by Alasdair Cochrane and Martha Nussbaum (which Fasel analyses in chap. 5). Meritocratic accounts seek to unseat the Aristocratic claim that humans are special, but Fasel argues that in doing so they result in an objectionable inequality: they imply that vulnerable humans should receive an inferior status due to their different capacities and interests (pp. 99–105).
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.087 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".