Mnemonic Fakery and Other Interpretive Strategies: Reclaiming Shingwauk Hall through Ethical Spectacle
Bibliographic record
Abstract
Providing a glimpse of the ongoing wrestle with ethics and practice involved in the Reclaiming Shingwauk Hall exhibition, an iterative residential school Survivor-led reclamation project, this article considers critical methods for implementing museal projects reckoning with difficult knowledge, and the ethical latitude they require. Doing so, it discusses risks of misrepresentation/recognition and the necessity of hopeful wounding, exposing the manipulations, fakery, and the prosthetic memories that exhibitions with great affective force produce. Exploring a range of exhibition-focused museal strategies that seek both to redress and prevent the recurrence of genocide and mass violence, this article articulates the tensions between i) affective power and cultural safety, ii) absence and presence, and iii) prosthetic and “authentic” memory that permeate the process of exhibition design. Returning to the evidentiary landscape of the Shingwauk Indian Residential School, interventions hybridizing examples discussed, putting them into the service of Survivors, offer a direction for future reclamation.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| 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".