Indigenous stewardship: lessons from yesterday for the parks of tomorrow
Bibliographic record
Abstract
Most researchers today acknowledge the impact of Indigenous populations on the supposed 'natural' or 'pristine' environments encountered by European explorers and naturalists travelling through the interior of North America.However, few are willing to accept the extent of this landscape management, especially in western North America.In fact, Indigenous populations created their own series of 'parks' through species-level, community-level and landscape-level management strategies such as the manipulation of plants, the selective harvest and displacement of resources, and the use of controlled burns.The resultant 'parks' were scattered across southern Alberta and were the product of disturbance and contingency guided by Indigenous perceptions of the reciprocal relationship between humans and the world around them.Using examples of managed landscapes scattered across southern Alberta, we discuss the origin of these Indigenous preserves and outline the motivation behind their stewardship.The lesson learned from this Indigenous approach to stewardship, we believe, provides guidelines for the management practices of tomorrow.
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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 | 0.001 | 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 | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".