Learning the Language of the River: Understanding Indigenous Water Governance with<i>O-Pipon-Na-Piwin</i>Cree Nation, Northern Manitoba, Canada
Bibliographic record
Abstract
Hydroelectric “development” in Canada has been criticized for the lack of meaningful consideration of community perspectives. This article shares the case of the O-Pipon-Na-Piwin Cree Nation (OPCN) in northern Manitoba, Canada, and the impact of mainstream water resource management strategies over their culture and livelihood. Through consideration of Kistihtamahwin, OPCN’s concept of water governance, as well as the promises made in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), this article argues that the lack of meaningful consultation and engagement with local resource users as well as the concept of Kistihtamahwin has led to the destruction of a successful fishery, which resulted in severe socioeconomic loss, environmental degradation, and cultural loss in the community. We found that for meaningful application of UNDRIP in Indigenous water governance, local cultural strategies and traditional knowledge are essential.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.028 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".