Restorying Relationships and Performing Resurgence: How Indigenous Storytelling Shapes Residential School Testimony
Bibliographic record
Abstract
This dissertation argues that an understanding of Indigenous storytelling can change how audiences engage with residential school survivors’ testimonies. From 2009 to 2015, Canada’s Truth and Reconciliation Commission (TRC) recorded residential school survivors’ stories. The National Centre for Truth and Reconciliation published these recordings online to meet survivors’ desire for their stories to be a learning opportunity. Any audience’s learning process is, however, contingent on their understanding of testimony. The most prominent Western understandings of testimony come from the contexts of courtroom testimony and trauma theory. Their theoretical underpinnings, however, emerge from epistemologies that are often incommensurable with Indigenous epistemologies, which can lead to a misreading of residential school testimonies. Looking at residential school testimonies through the lens of Indigenous oral storytelling, an inherently relational practice that creates and takes care of relationships, is an ethical alternative that allows audiences to recognize how these testimonies are a future-oriented process and restore relationships and responsibilities. My main argument is that Indigenous literatures can teach us how to apply the principles of Indigenous storytelling to residential school testimony. Indigenous epistemologies understand theory as a way of explaining processes by enacting those processes. Based on this, I argue that residential school novels reflect on the process of telling residential school stories by way of telling them. Thereby, the novels create theories of residential school testimony that explain how this form of testimony employs Indigenous storytelling principles in order to restore relationships that support Indigenous resurgence. I analyze residential school novels by Tomson Highway (Cree), Robert Arthur Alexie (Teetl’it Gwich’in), Richard Wagamese (Anishinaabe), and James Bartleman (Anishinaabe) in order to demonstrate how they re-imagine testimony by drawing from Indigenous storytelling principles that emphasize relationality, collectivity, and reciprocal responsibility. By applying the novels’ theories to the recordings of TRC testimonies, this dissertation renders visible how survivors used their testimony to create relationships, address contemporary political issues, and work towards Indigenous resurgence. Thereby, this dissertation contributes to a new understanding of testimony that enables audiences to engage with survivors’ stories in a decolonial manner.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.022 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".