Values-Based Approaches to Intercultural Conservation Around Lac La Ronge, Saskatchewan
Bibliographic record
Abstract
Across Canada, boreal woodland caribou (Rangifer tarandus caribou), are listed as “threatened” under the Canadian Species at Risk Act. Because the caribou have importance for many Indigenous and Euro-Canadian groups, they may especially benefit from intercultural approaches to their conservation. While Indigenous knowledges are increasingly sought after in natural resource research and management in northern Canada, Euro-Canadian government agencies face challenges with incorporating these from research into policy, such as how to weave Indigenous knowledges into boreal caribou conservation processes. The ongoing challenge of working across worldviews and, for Euro-Westerners, with Indigenous cultural or spiritual values that guide Indigenous Peoples’ relationships with other species, may still prevent or hinder progress toward protecting caribou together. Previous conservation policy has been limited to Indigenous knowledges that are most similar to that from the Euro-Western sciences – knowledge about things. This study takes an ontological and values-based approach to examine caribou conservation around Lac La Ronge, a large boreal lake in subarctic Saskatchewan. Affirming the Algonquian recognition of multispecies and multisentient actors, and through ethnographic and visual arts-based methods, the study documents Woodland Cree and Métis values regarding woodland caribou and intercultural conservation around Lac La Ronge, and considers their use and compatibility with existing Euro-Canadian conservation strategies. Findings highlight ontological differences between Indigenous and Euro-Canadian cultures as central to challenges of intercultural knowledge pairing, and, by extension, to the success (or failure) of intercultural conservation processes for woodland caribou more generally. The study produces a set of guiding principles and recommendations for conservation processes through a holistic, values-based framework, offering tools for weaving together multiple knowledge systems and creating ethical space for collaboration. Building on previous research that has begun to document Indigenous values regarding boreal caribou in Saskatchewan and across Canada, and adding to ongoing intercultural management efforts in Saskatchewan, these findings and recommendations have implications for developing more equitable and sustainable intercultural and interspecies relationships in Saskatchewan and elsewhere.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.017 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".