“This Is Going to Affect Our Lives”: Exploring Huu-ay-aht First Nations, the Government of Canada and British Columbia’s New Relationship Through the Implementation of the Maa-nulth Treaty
Bibliographic record
Abstract
Abstract Canada celebrated its 150th anniversary since Confederation in 2017. At the same time, Canada is also entering an era of reconciliation that emphasizes mutually respectful and just relationships between Indigenous Peoples and the Crown. British Columbia (BC) is uniquely situated socially, politically, and economically as compared to other Canadian provinces, with few historic treaties signed. As a result, provincial, federal, and Indigenous governments are attempting to define ‘new relationships’ through modern treaties. What new relationships look like under treaties remains unclear though. Drawing from a comprehensive case study, we explore Huu-ay-aht First Nations—a signatory of the Maa-nulth Treaty, implemented in 2011—BC and Canada’s new relationship by analysing 26 interviews with treaty negotiators and Indigenous leaders. A disconnect between obligations outlined in the treaty and how Indigenous signatories experience changing relations is revealed, pointing to an asymmetrical dynamic remaining in the first years of implementation despite new relationships of modern treaty.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.059 | 0.035 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| 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".