The River’s Legal Personality: A Branch Growing on Canada’s Multi-Juridical Living Tree?
Bibliographic record
Abstract
Relationships with rivers in British Columbia are imbued with social and material toxicity. Learning from the three legal systems British Columbians live with, Canadian, Indigenous, and international law, this paper offers a potential remedy to these imbalanced relationships by declaring the rights of nature in accordance with each system’s socio-cultural and doctrinal frameworks. Cross-cultural and inter-legal discussions guide the ontological multiplicities that cultivate the emergence and declaration of rivers’ legal personalities. Taking seriously storied precedents within Indigenous legal systems as modes of reasoning, learning from the ‘Namgis, Heiltsuk, and W̱SÁNEĆ Nations offers lessons for water relations. In expanding Canadian conceptions of personhood, challenging anthropocentrism within section 7 of the Charter, and working within but expanding section 35 constitutional protections, this discussion also accounts for the strategic use of Canadian legal concepts and protections for river relations. Drawing upon the international political and legal sphere, namely the United Nations Declaration on the Rights of Indigenous Peoples, helps advance rivers’ legal personalities. Braiding these three legal systems makes transparent the need for a reorientation in how we understand the rights of nature, namely through understanding and framing subsequent rights of nature developments through the prism of the multi-juridical living tree.
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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 | 0.003 |
| Science and technology studies | 0.040 | 0.017 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".