Bibliographic record
Abstract
In 2008, the Canadian government established a Truth and Reconciliation Commission (TRC) to review the history of the residential school system, a brutal colonial project that killed and injured many Indigenous children and left a legacy of trauma and pain. In Fragments of Truth Naomi Angel analyzes the visual culture of reconciliation and memory in relation to this complex and painful history. In her analyses of archival photographs from the residential school system, representations of the schools in popular media and literature, and testimonies from TRC proceedings, Angel traces how the TRC served as a mechanism through which memory, trauma, and visuality became apparent. She shows how many Indigenous communities were able to use the TRC process as a way to claim agency over their memories of the schools. Bringing to light the ongoing costs of transforming settler states into modern nations, Angel demonstrates how the TRC offers a unique optic through which to survey the long history of colonial oppression of Canada’s Indigenous populations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.027 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.032 | 0.005 |
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".