Templates and exclusions: victim centrism in Canada's Truth and Reconciliation Commission on Indian residential schools
Bibliographic record
Abstract
In this article I use an ethnographic approach to consider the causes and consequences of a focus on ‘survivor’ experience in Canada's Truth and Reconciliation Commission (TRC) on Indian residential schools. In this Truth Commission, the interconnected concepts of ‘survivor’, ‘cultural genocide’, ‘trauma’, and ‘healing’ became reference points for much of the testimony that was presented and the ways the schools were represented. Canada's Truth Commission thus offers an example of the consequences of ‘victim centrism’, including the ways that ‘truth‐telling’ can be influenced by the affirmation of particular survivor experiences and the wider goal of reforming the dominant historical narrative of the state through public education. Canada's TRC was limited by its mandate to a particular kind of institution and scope of collective harm. It was at the same time active in its creation of narrative templates, which guided the expression of traumatic personal experience and affirmed the category of residential school ‘survivor’ as the focal point for understanding policy‐driven loss of language, tradition, and political integrity.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.065 | 0.062 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".