Indigenous rights in national parks: The United States, Canada, and Australia compared
Bibliographic record
Abstract
National Park systems across the globe enjoy broad public support as custodians of many awesome specimens of nature's majesty and protectors of our most popular public pleasure grounds. However, the traditional inhabitants of these lands are seldom enamored with the concept. This is because the preservation of these places for the enjoyment of all has conventionally entailed the outright expulsion of an original few. In many cases native people who cherished deep spiritual connections to these lands for generations were suddenly prohibited from utilising traditional homesteads, hunting grounds, and sacred ceremonial sites. Gradually, the dominant common law governments of many nations have come to realise that restoring customary resource use regimes, management rights, and even outright traditional ownership of these lands is not only just but can help advance their common interests. This paper utilises a comparative law approach to assess indigenous natural resource use and land management rights in the national parks of the United States, Canada, and Australia. It concludes with an assessment of each nation's compliance with the United Nations Declaration on the Rights of Indigenous People, an agreement the three nations each initially rebuked but have since come to endorse in their administration of national parks.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".