The Inuit presence at the first Canadian Truth and Reconciliation Commission national event
Bibliographic record
Abstract
This paper addresses various forms of healing and reconciliation among Canadian Inuit and First Nations, in regards to the Indian residential school system and the Truth and Reconciliation Commission (TRC). Stemming from fieldwork at the TRC’s first national event in Winnipeg (June 2010), I present observations that are supplemented by previous studies on Aboriginal healing methods in Canada. Although Inuit and First Nations healing and reconciliation strategies are based on common themes—tradition and community—in practice they diverge notably, both in their principles and in their applications. First Nations seek healing by activating a sense of community that often transcends their specific cultural group or nation, using pan-Indian spiritual traditions and ceremonies. In contrast, the Inuit most commonly seek to preserve and promote specific Inuit traditions and identity as tools in their healing practices. This divergence could be seen in Inuit and First Nations’ participation in the TRC. The creation of the Inuit sub-commission within the TRC in March 2010, resulting from intense lobbying by Inuit leaders, was a first sign of the group’s distinctive approach to healing. But the unfolding of the TRC’s first national event in Winnipeg showed again how these differences materialise in practice and contribute to a better understanding of Inuit responses to the repercussions of their colonial past and strategies for healing from the legacy of residential schooling.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".