Pursuing Justice:The Criminal Liability of the Christian Clergy in the Cultural Genocide of Indigenous Peoples in Canada and Australia
Bibliographic record
Abstract
Indigenous populations often bore the brunt of Christian settler colonization resulting in marginalization, assimilation, Christianization, and cultural elimination. Most perpetrators of colonial injustices go unpunished and wrongdoings unacknowledged, barring the possibility of genuine international and national reconciliation for indigenous peoples. Major settler colonizer states have dark colonial histories regarding the treatment of indigenous peoples, among which two renowned examples are the case studies of this thesis, the Canadian residential school system, and the Australian stolen generation child removals. These state-enacted assimilation policies prescribed forcible indigenous child removals to church-run educational and residential institutions. This research aims to explore the criminal liability of the Christian clergy members in the two assimilationist systems, through the establishment of a culturally-permissive interpretation of the UN Genocide Convention’s genocide definition. The thesis analyses the historical development of the codification of genocide, deciphers the elements and definitions of the crime and explores whether cultural genocide could be understood as part of the international criminal law framework on genocide. Additionally, it assesses whether the atrocities in Canada and Australia amount to a cultural genocide which could trigger the individual criminal liability of Christian clergy members who administered the destination institutions of the forcible child transfers. The thesis concludes that the UN Genocide Convention’s interpretation reasonably infers a cultural component to the definition of genocide and asserts that the atrocities in the Canadian residential school system and the Australian stolen generation child removals amount to cultural genocide. Further, the research suggests that the moral and practical assistance provided by the Christian clergy members in these two systems constitute aiding and abetting in the commission of cultural genocide, thereby triggering individual criminal liability. Lastly, the thesis advises that the best possible pathways for prosecuting members of the clergy would be through exercising universal jurisdiction in absentia.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".