Instructive Past: Lessons from the Royal Commission on Aboriginal Peoples for the Canadian Truth and Reconciliation Commission on Indian Residential Schools
Bibliographic record
Abstract
Abstract Over time, the Canadian state has used a variety of mechanisms to address its troubled relationship with its indigenous population, the most prominent of which so far was the Royal Commission on Aboriginal Peoples (RCAP). RCAP was mandated to develop both a constitutional framework and a comprehensive social-welfare policy. Staffed predominantly with constitutional lawyers, it articulated a sophisticated constitutional theory, which was not implemented, and did little to ameliorate the living conditions of Aboriginal people. The Truth and Reconciliation Commission on Indian Residential Schools (TRC), while arising from the settlement of a national class action, can be seen as a successor commission to RCAP. It follows in the procedural footprints of RCAP in a number of ways, including in the profile of its key appointments. This article argues that looking back at the successes and failures of RCAP can be instructive for the TRC as it carries out its mandate, allowing us to predict some areas that will be particularly challenging. In these areas, the TRC will require a departure from the RCAP blueprint if it is to achieve the ambitious goals of a TRC in a non-transitional-justice 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 | 0.029 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.057 | 0.043 |
| Scholarly communication | 0.028 | 0.007 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.011 | 0.018 |
| Insufficient payload (model declined to judge) | 0.011 | 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".