Bibliographic record
Abstract
Abstract In the last 20 years the native people of Canada have asserted their sovereignty by rejecting their status as wards. Their subordination had caused removal of their children to boarding schools to remerge as imitation white adults. It involved the purging of their own culture, including language, names and religious symbols. There is now evidence that there were thousands of preventable deaths in these schools, because the conditions were criminally negligent and the teaching was backed up by corporal punishment. In response to these allegations the Canadian government has set up a Truth and Reconciliation Commission, but it lacks any investigative or punitive powers. As it has no right to compel witnesses, the First Nations have established their own International Human Rights Tribunal into Genocide in Canada (IHRTGC). This has the objective of presenting evidence to the United Nations in order for a court to be empowered on lines of an international tribunal investigating crimes of ethnic cleansing to try the officials of the government and the Churches. Will the redress the IHRTGC is seeking stand the test of evidence that proves beyond reasonable doubt the culpability of the accused? Can the appropriation and abuse of aboriginal children be abated? What kind of compensation will be payable once guilt has been proved?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".