Cultural genocide in Australia, Canada, New Zealand, and the United States
Bibliographic record
Abstract
This article focuses on the impact of cultural genocide on the Indigenous populations of four former English colonies--Australia, Canada, New Zealand, and the United States of America (USA)--and current efforts to heal the wounds caused by this genocidal activity. Cultural genocide is much more widespread and ongoing than the murder of ethnic minorities, and in the four countries under discussion government policies promoted English-only schooling and conversion to Christianity, making schools instruments of cultural genocide. If indigenous students resisted, they were further marginalized and if they attempted assimilation they often found that their skin color still excluded them from full citizenship. Some people think that democracies are immune to genocide, but through the “tyranny of the majority” laws can be passed that suppress minority languages and cultures as do the various “English-only” and “Official English” laws in effect in some states in the USA today (e.g. Crawford 2000). Lemkin in his original discussion of genocide included the “prohibition of the use of their own language by the population of an occupied country” (Lemkin 1944, ix). The 1868 Report of the U.S. Indian Peace Commission stated, “Schools should be established, which [American Indian] children should be required to attend; their barbarous dialect should be blotted out and the English language substituted.” Besides suppressing indigenous languages, colonial governments suppressed Indigenous cultural practices, including Potlatches, Sun Dances, and other religious activities
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".