The Work that Remains: Continuing the Reconciliation Work of Legal Tribunals through Museums
Bibliographic record
Abstract
There is no substitution for seeing something with your own eyes. Attending the Woodland Cultural Centre and touring the Mohawk Institute added an indelible texture to the TRC Workshop and to my thoughts about the long-term work of truth and reconciliation. Seeing the physical space where children were held, abused, and some killed, and meeting and listening to the experiences of survivors has brought an urgency to my work that no amount of reading these histories in books and journals could ever do. Even though I had attended the Truth and Reconciliation Commission of Canada event in Montreal in 2013 and listened to dozens of people testify about their experiences in residential schools, there was something different about being in the very place where the children had lived. While I can empathize with the desire of some student-survivors to destroy the physical buildings where such widespread harm was inflicted, as an outsider I gained a new level of understanding from seeing the space, and I hope that these buildings will be preserved so that generations of people may also do so.
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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 | 0.021 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.064 | 0.058 |
| Scholarly communication | 0.025 | 0.027 |
| Open science | 0.005 | 0.034 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".