Editorial Address & Advisory Board
Bibliographic record
Abstract
The second issue of volume five of the Journal of the Council for Research on Religion (JCREOR) is a special issue, From Indigenous ‘Religions’ to Indigenous Values. Planned and realized in collaboration with Philip P. Arnold (Syracuse University), the Indigenous Values Initiative (IVI), and the American Indian Law Alliance (AILA), this volume offers a collection of responses and articles that speak to the themes and tensions noted in the Report on Indigenous Religious Freedom or Belief, presented by the United Nation’s Office of the External Special Rapporteur on Religious Freedom or Belief, which we have gained special permission to republish here in full. This issue provides input on the report but also examines the restrictions and limitations imposed by the categories of religion and/or belief when working with Indigenous nations and communities. The responses to Special Rapporteur Ahmed Shaheed’s report discuss not only the usefulness of the categories of religion and belief but also their limitations, which hinder much-needed discussions about Indigenous values and sovereignty. The articles address the historical injustices faced by Indigenous nations and communities in the name of religious freedom, the need for decolonial approaches to the study of religion, and the colonial tensions created by the categories of religious freedom and belief and their relationship to the Doctrine of Christian Discovery. The issue concludes with a reflection by the Special Rapporteur.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.342 | 0.262 |
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".