On the Limits of the Concept of Religious Freedom in Indigenous Communities
Bibliographic record
Abstract
In this essay, we will argue that firstly, the international and national legal framings of religion or belief are limited in scope, and one must ask not only religious freedom for whom but also from whom. Secondly, we will underscore the continued limitations of international human rights-based discourse. Why are Indigenous nations consistently excluded from rights-based discourses? We have the UN Declaration on Human Rights (UNDHR), the UN Declaration on the Rights of Indigenous Peoples (UNPFII), the Expert Mechanism on the Rights of Indigenous Peoples (EMRIP), this new report, and so many other reports. We will ask at what stage we move from declarations and reports to protecting and supporting Indigenous nations and peoples. Thirdly, building on the limitations of rights-based reporting, we will highlight what this report gets right and invite activists, lawyers, scholars, and all folks to take up and read the report and follow up on the elements we believe to be most salient. Finally, we will conclude by offering an alternative to declarations that support Indigenous nations and peoples’ inherent right to sovereignty. Our conclusion emphasizes Faithkeeper Lyons' urgent message, “The Ice is Melting in the North,” and provides a framework for how people could respond by explaining the Two Row Wampum treaty and the Two Row Wampum Method.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.087 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| 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".