Indigenous knowledge‐bridging to support ecological stewardship in Canada and Tanzania
Bibliographic record
Abstract
Abstract Indigenous peoples worldwide assert their cultural and political governance through ecological stewardship and traditional land use. With the rapid degradation of ecosystems globally, there is a growing need to strengthen the role of Indigenous knowledge systems and values in environmental stewardship. One promising yet understudied way to meet this need is through knowledge‐bridging. We explore how international knowledge‐bridging fosters solidarity in the ongoing struggle for Indigenous self‐determination and resource rights. Drawing from exchanges between Maasai communities in Tanzania and First Nations in British Columbia and the Yukon, we examine how Indigenous groups assert their roles as environmental stewards through distinct governance systems. Despite Indigenous communities being embedded in vastly different histories and political contexts, our research highlights shared concerns about climate change and other stressors, underscoring the urgency of knowledge‐bridging and strengthened connections. Bridging Indigenous knowledge systems in environmental stewardship diversified ecological governance perspectives by fostering mutual support and learning. Our work highlights the ecological relevance of upholding cultural teachings that promote sustainability through arts‐based methods and participatory videography for contextually relevant storytelling. Participatory video proved to be an accessible and powerful tool for cross‐cultural knowledge exchange. Follow‐up interviews affirmed the impact of this method, revealing how Indigenous participants felt empowered and motivated to support co‐learning in the context of growing pressure on nature and its resources. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".