Contribution of Land-Based Knowledge of Cumberland House to Ensure Water Security, Food Security, and Ecological Justice.
Bibliographic record
Abstract
The Northern Métis Village of Cumberland House, the oldest Métis community in Western Canada, is located within the Saskatchewan River Delta (SRD) and faces severe water security challenges. These issues stem from long-standing environmental degradation caused by colonial development practices, particularly the construction of upstream hydropower dams such as the E.B. Campbell, Gardiner, and Francois Finlay dams. Rooted in Western economic ideologies, these projects ignored the Traditional Ecological Knowledges (TEK) of Indigenous peoples, leading to irreversible ecological damage and disrupted hydrological patterns in the delta. This research employs a Community-Based Participatory Research (CBPR) approach to explore the impacts of water insecurity on the physical, mental, and spiritual well-being of the Cumberland House community. Data were collected through semi-structured interviews and observations involving community elders, members, and environmental experts. Findings reveal that dam operations have caused unpredictable water levels, biodiversity loss, food insecurity, and restricted access to safe drinking water and traditional harvesting sites. The study highlights that integrating Indigenous Land-Based Knowledges with Western scientific approaches offers a sustainable Two-Eyed Seeing approach (Bartlett et al., 2012), essential for realizing ecological justice, food security, and a balanced relationship between environment and community. Embracing TEK in water governance and policymaking can help ensure ecological justice, food and water security, and a more balanced relationship between environment, economy, and equity in Cumberland House.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".