Bibliographic record
Abstract
In Canada, historical treaties were negotiated between the Crown and Indigenous Peoples to secure the peaceful settlement of lands and facilitate resource development. Treaty #8 is one of the historic treaties that assures its adherent First Nations of their rights to hunt, fish, and trap throughout the territory covered by the document. The treaty also allows for the taking up of lands by the provinces for settlement, mining, lumber, trade, or other purposes. While treaties in general, and Treaty #8 in particular, were intended to enable reconciliation, it has instead been the subject of several court cases. One of these cases is Yahey v. British Columbia ,, in which Chief Marvin Yahey, on behalf of Blueberry River First Nations (BRFN), successfully sued the province of British Columbia (BC) on the cumulative effects of industrial development on BRFN’s treaty territory. In the verdict, issued in June 2021, the Supreme Court of British Columbia ruled that by authorizing industrial development, the province of BC breached its obligation to BRFN under Treaty #8. As a result, the province could not continue to authorize activities that breach Treaty #8 and its unwritten promises without meaningfully engaging with the Nation. Within the context of meaningful stakeholder engagement, this chapter is a case study of Doig River First Nation (DRFN), a Treaty #8 First Nation with a shared history of land use with BRFN. In this contribution, it is explained how engagement for the purposes of resource development will need to shift post- Yahey from transactional consultation leading to project approval by the province, to meaningful community engagement with the goal of achieving First Nation consent and reconciliation.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.058 | 0.014 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.048 | 0.004 |
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".