Investigation of the Tribal Park Concept and Opportunities for the Blackfeet Nation
Bibliographic record
Abstract
The Tribal Park model is an emerging tool being used by indigenous groups in the United States and Canada for the management of unique and sacred natural areas, in some cases setting aside existing indigenous owned land, and in others regaining control of land management decisions in traditional territory. Currently in North America there are several sites that have self-identified as Tribal Parks. There is a lack of research regarding Tribal Park development in North America, which creates challenges for indigenous groups interested in pursuing a conservation designation of this type. Using an analysis of five Tribal Park case studies this thesis identifies the key components of these Tribal Parks. Specifically focusing on the economic, cultural, and ecological aspects of each case study. This research then uses interviews with members of the Blackfeet Nation, to explore the potential interest in a Tribal Park on Blackfeet Nation lands. This study finds that though the Tribal Park concept varies across case studies based on the needs of the specific community, there are some important common aspects across cases. These aspects include: a bottom-up community driven planning process with programs in place to increase capacity of community members, exercising sovereignty over land-use decisions in traditional territory, and connectivity of landscapes and habitat protection. Some of the themes identified by Blackfeet Nation respondents were potential benefits from capturing visitor overflow from neighboring Glacier National Park, increased access to land by community members, and concerns regarding land-use conflicts between different user groups.
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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 | 0.003 | 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 | 0.015 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".