Whales and Seals and Bears, Oh My! The Evolution of Global Animal Law and Canada's Ambiguous Stance
Bibliographic record
Abstract
This chapter looks at the emergence of a new perspective on animals in international law, and the Canadian government's position vis-a-vis this development. We articulate three main propositions. First, although animal protection used to be thought of as mainly or even solely a domestic matter, it is becoming a recognized (although still nascent) field in international law, so much so that scholars are now paying serious attention to a phenomenon called “global animal law.” Second, the record on Canada's participation in this growth of global animal law has been decidedly mixed, and on balance Canada has been more obstructive than supportive. While the government has provided some limited and symbolic support for global animal welfare initiatives regarding domestic animals, it has actively opposed the development of progressive international norms with respect to certain wild species that are subjects of particular concern in international law: whales, seals, and polar bears. Our third proposition reflects our attempt to explain why this second proposition is the case. We posit that the limit to Canada's support of emerging global animal law is found where international efforts to promote animal protection conflict with the government's perceived political interests, and where these efforts lead to difficult tensions in Canada's relationship with its Indigenous peoples. This is not to suggest, of course, that Canadians are on the whole opposed to stronger international protection for animals, nor to downplay the important contribution of Canadian-based civil society organizations to the international movement to curtail exploitation of whales, seals, and polar bears, and still less to deny the deep affinities that do exist between progressive international norms regarding animals and the way Canadian Indigenous peoples conceptualize ethical relationships between humans and animals.4 Rather, what we want to convey is that the Canadian government's position on these issues is driven by its chosen strategy for bargaining with certain politically influential or sensitive geographically constituted interest groups, and its decision to sign on to the rhetoric used by some leaders of those groups regarding hunting and wildlife exploitation. By making those choices, Canada's government has led this country away from its traditional place as a leader in the development of international norms, a decision that has been exacerbated by the Harper government's more general rejection of international law.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.041 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".