Thoughts and Prayers: Comparing Public Apologies for Residential Schools in Canada
Bibliographic record
Abstract
Apologies are politically fraught. The act of publicly naming an issue and offering an apology is something that is increasingly called for and received within Canadian federal politics. Prime ministers have increasingly engaged in apology work, particularly in relation to the ongoing impacts and consequences of settler colonialism. In the shadow of the Truth and Reconciliation Commission and Final Report, the necessity of owning and giving voice to responsibility for violence perpetrated by the Canadian state against Indigenous children, families, and nations is increasingly obvious. The spring and summer of 2021 have brought about the research (both ground- penetrating software and archival) to relocate suspected previously unrecorded and/or unmarked burials of Indigenous children on the grounds of former residential schools. Prime Minister Stephen Harper’s 2008 apology for residential schools marked an important first apology by a sitting prime minister for residential schools. In 2021, Prime Minister Justin Trudeau offered a more informal apology, in the aftermath of the research to relocate potential unmarked burial sites at residential schools. These two apologies offered by sitting Canadian prime ministers regarding residential schools occur on either side of the important event of the Truth and Reconciliation Commission, socially and politically coordinating the discourse of reconciliation. This research study examines the texts of the 2021 and 2008 public apologies for residential schools to render visible the often-disappeared patterns and conventions of the language and context of settler apology. This paper picks up the “age of apology” and questions whether the contemporary state responses to the suspected unmarked graves at residential schools demonstrate the continuation or the recession of the deployment of public apology as the major vehicle of settler colonial discourses of reconciliation. Ultimately, based on a comparison of these two apologies, this paper argues that official state apologies remain largely performative. Despite the transformative impacts of the commission, the “age of apology” persists, evidenced by similar strategies and discursive markers in apologies issued by prime ministers both before and after the commission and final report. This study examines the continuity of apology politics and the role these apologies hold in perpetuating settler obfuscation of responsibility in ongoing colonial violence.
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.027 | 0.016 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".