Nature's rights are human rights: revitalizing Indigenous land stewardship through legal personhood
Bibliographic record
Abstract
Indigenous peoples have held rich, complex knowledges on environmental sustainability and the interrelatedness of humans and the natural world since time immemorial. However, this expertise continues to be largely excluded within domestic and international environmental decision-making. In recent years, a strategy has emerged which provides opportunity for Indigenous worldviews about the environment to be strengthened within a legal context. Legal personhood involves assigning legal rights and protections to natural entities, like rivers. This concept challenges current human rights discourse to include Indigenous knowledges on how the wellbeing of the environment and human beings is not only linked but mutually dependent. This paper provides connections from human rights foundations, theory, and practice to the legal personhood method, as researched during my practicum at Wa Ni Ska Tan. Finally, this paper indicates the potential for the legal personhood method to revitalize Indigenous land stewardship and autonomy in Canada, and advocates for the necessity of further research, education, and awareness on this process.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.044 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".