Defending Land and Water: Using Customary International Law to Advance Indigenous Rights in Settler Canadian Law
Bibliographic record
Abstract
Canada has been gradually working towards implementing the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP). Recent case law from the Supreme Court affirms that UNDRIP is an interpretative source for Canadian law, but the impact of UNDRIP on constitutional jurisprudence, particularly section 35, remains an open question. While UNDRIP is a non-binding declaration, certain articles of the Declaration may be considered to represent customary international law (CIL). This includes Article 25, which recognizes the right of Indigenous Peoples to “maintain and strengthen their distinctive spiritual relationship with their traditionally owned or otherwise occupied and used lands, territories, waters and coastal seas and other resources and to uphold their responsibilities to future generations in this regard.” I argue that Article 25 of UNDRIP is CIL and therefore binding on Canada. Indeed, I argue that Article 25 bridges a gap that currently exists in Canadian law wherein spiritual rights and the protection of territory are seen as distinct, thereby excluding claims by Indigenous Nations and communities who seek to protect their sacred territories. I do so by analyzing existing domestic and international case law on CIL, with a focus on the kinds of evidence and arguments considered by Canadian courts when weighing whether or not a binding custom exists.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.018 | 0.029 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".