Bibliographic record
Abstract
This article critically examines the use of science in the formation of global animal law. It focuses on two international legal decisions that made a significant contribution to the development of global animal law in 2014: the report of the Appellate Body of the World Trade Organization (WTO) in EC – Seal Products, and the judgment of the International Court of Justice (ICJ) in Whaling in the Antarctic. The authority of science, and the interaction between scientific and juridical methods, lie at the heart of both of these decisions. In Whaling in the Antarctic, the ICJ ruled that Japan’s whaling programme in the Southern Ocean is not ‘for purposes of scientific research’ within the meaning of the International Convention on the Regulation of Whaling. In EC – Seal Products, the WTO Appellate Body ruled that the European Union’s ban on seal products was justifiable under Article XX(a) of the General Agreement on Tariffs and Trade as a matter of public morals because it was based on European citizens’ moral objections to cruelty in seal hunting. Both cases, as well as the controversies over whaling and sealing that led up to them, illustrate the persuasive power of the ‘appeal to science’, enlisting scientific objectivity and rigour to underpin the credibility of legal arguments. At the same time, both judgments vindicate the final authority of jurists to determine questions of justice and confirm that such questions cannot be simply outsourced to science. The article analyses the way science is used in the reasoning of both tribunals and finds that both decisions appropriately distinguish between the roles of scientific and legal reasoning. It concludes by proposing, following the direction suggested by Judge Cançado Trindade’s separate opinion in Whaling in the Antarctic, that the basis of international obligations towards animals is to be found not so much in scientific evidence as in our shared humanity and ethical conscience.
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 | 0.029 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.074 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.015 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 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".