Contesting reconciliation, foregrounding relationality:contemporary Indigenous women’s writing in Canada
Bibliographic record
Abstract
In an era of ‘reconciliation’ marked by the work of Canada’s Truth and Reconciliation Commission (TRC), active from 2008 to 2015, this thesis examines how contemporary Indigenous women’s writings challenge and rethink established models of testimony and relationality. It explores how Lee Maracle (Stó:lō), Katherena Vermette (Métis), Tracey Lindberg (Cree), Terese Marie Mailhot (Nlaka’pamux), and Norma Dunning (Inuit) widen understanding of testimony in imaginative, personal, and collective ways through novels, life-writing, and short stories in which the dominant tenets of reconciliatory discourse advocated and advanced by the TRC can be seen to be challenged and complicated. Focussing on mutual understanding, attentive listening, anger, pain, empathy, forgiveness, and healing, this thesis intervenes in and expands discussions of ‘reconciliation’ and puts under scrutiny a colonial narrative of ‘Indigenous deficiency’ and the role of epistemic injustice in Indigenous-settler relations. Its theoretical lens is wide, encompassing Indigenous theory, postcolonial studies, queer theory and affect studies, and an interdisciplinary approach to literary analysis that draws on adjacent fields of philosophy, sociology, politics, law, and health studies. It argues that selected literary texts authored by Indigenous women offer alternative and more equitable pathways for establishing, mending, and nurturing meaningful relationships between Indigenous peoples, settlers, and other beings on the land. These pathways chart forms of engagement that require an accommodation of refusal and a respect for complexities and opacities. This thesis contributes to a growing body of literature that centres the voices of contemporary Indigenous writers and emphasises the importance of storytelling in illustrating alternative forms of action and healing.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.054 | 0.037 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".