What Does Genocide Produce? The Semantic Field of Genocide, Cultural Genocide, and Ethnocide in Indigenous Rights Discourse
Bibliographic record
Abstract
The semantic field of genocide, cultural genocide, and ethnocide overlaps between Indigenous rights discourse and genocide studies. Since the 1970s, such language has been used to express grievances that have stimulated the construction of Indigenous rights in international law. These particular words signify general concerns with the integrity of Indigenous peoples, thereby undergirding a larger framework of normative beliefs, ethical arguments, and legal claims, especially the right to self-determination. Going back to the post-World War II era, this article traces the normative and institutional processes through which this overlapping discourse has emerged. Culminating with the adoption of the 2007 United Nations Declaration on the Rights of Indigenous Peoples, this process of international lawmaking has critically challenged the conventional interpretation of genocide, especially as the latter has been categorically distinguished from cultural genocide or ethnocide.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.067 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".