US Federal Off-Reservation Boarding Schools and Ethnocide's Benevolent Perpetrator
Bibliographic record
Abstract
The United States federal off-reservation Indian boarding schools of the twentieth century have been the locale for ethnocide and cultural genocide of the Native American population. While in any critical discussion of mass atrocity crimes, such as genocide and ethnocide, the question of the perpetrators always ranks central, not much attention has been paid to the perpetrators of ethnocide who operated in these off-reservation boarding schools. Furthermore, scholarship has focused on perpetrators in genocide but has not spent much time considering the definitional nuances between perpetrators in ethnocide and genocide. In this paper, I highlight an additional perpetrator type that applies specifically to ethnocide, which is an addition to existing perpetrator typologies. This benevolent perpetrator, who is specific to ethnocidal crimes, can for instance be found in United States federal off-reservation Indian boarding schools between 1878 and 1934. Paying attention to these perpetrators and considering them as a unique type, will allow for furthering and developing our understanding of ethnocide, perpetration and complicity, and assimilation practices in off-reservation boarding schools. Furthermore, this discussion is embedded in the debate about the applicability of the terms genocide and ethnocide in a settler-colonial context.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| 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".