Rethinking Indigenous Hunting in National Parks
Bibliographic record
Abstract
Designed to be “wilderness” spaces with minimal human impact, the establishment of national parks contributed to dispossessing Indigenous peoples from traditional territories across North America, preventing access to dwindling populations of wildlife essential to cultural and material well-being. With the systematic near extermination of buffalo during the nineteenth century and forcible relocation of Tribes onto reservations, Tribal food systems collapsed. Tribal Nations across the Great Plains are now restoring buffalo to support food sovereignty and political resurgence, while re-asserting a presence in national parks where Indigenous hunting remains prohibited. This article focuses on the Blackfoot-led Iinnii Initiative working to restore free-roaming buffalo (Bison bison) along the Rocky Mountain Front, supported by Glacier and Waterton Lakes National Parks. Recognizing Tribal rights to hunt buffalo in these parks would enable Tribal hunters to exercise practices that challenge the idea of national parks as wilderness. We coproduce this article as Blackfoot and non-Indigenous scholars and activists, drawing on interviews with restoration practitioners, Blackfoot knowledge holders, and park and other government officials to explore distinct narratives of what it would mean to enable Tribal hunting in national parks, with implications for food sovereignty, political resurgence, and wildlife management. We argue that openness within parks agencies to Indigenous hunting suggests a potential watershed moment for reimagining the role of people in parks. Through this, we examine important links between food sovereignty, political sovereignty, biodiversity conservation, and decolonization.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".