kihci-ministik: Protecting our sacred waters in an age of climate change through land-based learning in Saskatchewan, Canada
Bibliographic record
Abstract
Protecting our sacred water has never been more important given the impacts of climate change. Although the importance of Indigenous Knowledge is increasingly recognized and valued by the Intergovernmental Panel on Climate Change, it is often dismissively fragmented and packaged into western science concepts of adaptation. This article recounts Indigenous Knowledge shared at a land-based camp using a decolonial Indigenous relational methodology imparted by engaging in land-based cultural practice and ceremony. Through methods of storytelling and deep listening, participants learned that Mother Earth’s bounty is medicine and medicine is not for sale. By engaging in ceremony and land-based practices, sacred relationships with water, land, and the stars as living entities (and not commodities) were rekindled and participants’ worldviews decolonized. But more than information was imparted in this manner; fundamental Indigenous laws important for addressing climate change and the era of the Anthropocene were experienced. Through the hard work of tanning hides participants engaged in a change process rooted in not only western science of biology but also Indigenous pedagogy of humility, open-mindedness, and connection. While Elders imparted knowledge of land-based learning, their storytelling and ceremony imparted holistic Indigenous Knowledge of interconnectedness with one another, the water, land, and stars. In solving climate change, the Elders have warned for some time of approaching hard times. The solutions reside with teachings and advice for relying on one another, honoring Mother Earth and her life blood, water. In this way, a new discourse, free of colonial, neoliberal underpinnings emerges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".