A Bridge to Reconciliation: A Critique of the Indian Residential School Truth Commission
Bibliographic record
Abstract
In the past year, the Government of Canada has established the Indian Residential Schools (IRS) Truth and Reconciliation Commission (TRC) to address the deleterious effect that the IRS system has had on Aboriginal communities. This paper argues that the TRC as an alternative dispute resolution mechanism is flawed since it focuses too much on truth at the expense of reconciliation. While the proliferation of historical truths is of great importance, without mapping a path to reconciliation, the Canadian public will simply learn about the mistakes of the past without addressing the residual, communal impacts of the IRS system that continue to linger. The Truth and Reconciliation Commission must therefore approach its mandate broadly and in a manner reminiscent of the Royal Commission on Aboriginal Peoples of 1996.
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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 | 0.044 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.037 | 0.102 |
| Scholarly communication | 0.027 | 0.016 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.017 | 0.029 |
| Insufficient payload (model declined to judge) | 0.004 | 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".