Ghosts of another world: voices from the non-Indigenous descendents of former Canadian residential school staff
Bibliographic record
Abstract
Based on Prime Minister Harper’s 2008 Apology for the Indian Residential School (IRS) system, this thesis addresses the need to confront the intergenerational legacy of this system on non-Indigenous Canadians in order to challenge our ability to actually ‘journey together’ with Indigenous Survivors. Aiming to break the silence that has surrounded this legacy, the voices of non-Indigenous descendents of former staff, as well as my own as a non-Indigenous Canadian, expose personal experiences of the lived reality of the IRS legacy. Working from a narrative methodology from within a decolonizing framework, this research includes interviews with two descendents of former staff, as well as an auto-ethnography of myself, as researcher, to capture the lived experiences with relation to this legacy. Results from this introductory work illustrate a variety of themes needing to be acknowledged, and deals with notions of opening dialogue, violence, guilt and responsibility within the context of the IRS system.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.096 | 0.033 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".