Kwayeskastasowin ᒃᐗᔦᔅᑲᔅᑕᓱᐎᓐ (Setting Things Right): Cree Pathways to Modernizing Treaty 9
Bibliographic record
Abstract
Treaty 9 stands at a decisive crossroads where intensifying extraction pressures, notably Ontario’s Ring of Fire, collide with unresolved Indigenous sovereignty and governance. While signatories understood the treaty as a covenant of coexistence and shared stewardship, Canada imposed a land-surrender narrative, entrenching jurisdictional ambiguity, ecological degradation, and Indian Act dependency. This thesis advances a decolonial framework for treaty renewal by bridging Indigenous legal traditions, wahkohtowin, kaapimaacihkaawaatisiwin, and minopimaatisiiwin, with Canadian constitutional jurisprudence, legal pluralism, UNDRIP and FPIC standards, and comparative governance models. Its original contribution is the Treaty Modernization Toolkit, the first to operationalize Indigenous law into governance innovation through jurisdictional clarity tables, enforceable FPIC protocols, co-governance institutions, and accountability mechanisms. Combining Indigenous methodologies, relational accountability, and comparative analysis, this research contributes to critical political science, constitutionalism, and global Indigenous governance debates, equipping Treaty 9 rights holders with transformative pathways to reclaim inherent rights, protect lands, and sustain intergenerational nationhood.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".