The Conflation of the Justification Framework for Infringement of Aboriginal Rights with the Oakes Test in Tsilhqot’in Nation v British Columbia
Bibliographic record
Abstract
In Tsilhqot'in Nation v British Columbia, the Supreme Court of Canada replaced the test for the justification of Aboriginal rights infringements with a framework that is nearly indistinguishable from the Oakes test. The goal of this paper is to show that this development in the law, and thus the current justification framework, is undesirable and erroneous. This paper submits four reasons to arrive at this conclusion. First, the justification test proposed in Tsilhqot'in mirrors the test rrequired to prove an infringement of Aboriginal rights, whose burden of proof falls on the Indigenous party, and hence shifts the entire onus of proving justification from the Crown to the Indigenous party. Second, the conflation of the Oakes test with the justification framework makes justification effectively impossible, which may cause reluctance amongst courts to recognize Aboriginal rights. Third, Aboriginal rights are fundamentally different from Charter rights and should not be subjected to a test designed for the Charter. Fourth, the incorporation of the Oakes test into the justification framework runs contrary to established principles of constitutional interpretation. These four reasons merit abandoning the framework proposed in Tsilhqot'in. Otherwise, this area of the law will be riddled with doctrinal flaws and Indigenous interests will suffer.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.034 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".