Bibliographic record
Abstract
For those who hear of the testimony presented to Canada's Truth and Reconciliation Commission on Indian residential schools, it can be shocking to learn that the Government of Canada and the Anglican, Catholic, Presbyterian, and United Churches were responsible for a residential school policy that forcibly took tens of thousands of children from their families and incarcerated them in institutions with the intention of eliminating their distinct languages and ways of life.It can be especially troubling to learn about the prevalence of sexual abuse in these schools from those who, as children, were victimized by sexual sadists and about the lasting effects of their trauma into adulthood, within their families, and across generations.And for those who look further into the work of the TRC, it can be disturbing to learn that there was a lack of engagement in the process of recognition and reparation by the federal government for the harms of the schools, with minimal government participation in the TRC's events and obstruction of its access to official documents.These are the kinds of experiences and issues that, rightfully, easily capture our attention.But as the chapters in this book show, there is much to be gained by looking beyond the most prominent harms and controversies, beyond the obvious sources of sympathy, and beyond the compelling ideas that readily provoke compassion and indignation in order to also inquire into those issues and ideas that tell us more about the bigger picture, about such things as the place of the TRC in the history of human rights and transitional Foreword
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.728 | 0.713 |
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".