TSILHQOT'IN NATION v. BRITISH COLUMBIA
Bibliographic record
Abstract
The Tsilhqot'in case is the most recent Canadian case to contribute significantly to the jurisprudence concerning first peoples land rights. Explicit constitutional protection of Aboriginal land rights has existed in Canada since 1982. Without statutory guidance, particularly vexing issues with which the courts are grappling are firstly the concept of Aboriginal title and secondly evidentiary standards to prove such title that are both equitable and acceptable to the courts. This in turn has led the courts to reject some occidental land law concepts and embrace a sui generis approach to Aboriginal land rights and an approach to the law of evidence appropriate to Aboriginal tenure systems. To date a First Nation is yet to successfully claim Aboriginal title in Canada, and the Tsilhqot'in too were unsuccessful on first instance. However, the Tsilhqot'in judgment imparts a practical foundation for the judicial consideration of oral history and oral tradition evidence. Additionally, while the decision is not binding on cases that follow, the decision provides an indication of areas in which a claim for Aboriginal title might be successful. Moreover, whereas the idea of boundaries is a Eurocentric principle and the Tsilhqot'in have had to conform to those common law principles in order to simply make a claim; traditionally, the Tsilhqot'in society did not have any 'metes and bounds' boundaries but instead recognized something along the lines of social boundaries.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".