Review of <i>Unsettling the Settler Within: Indian Residential Schools,Truth Telling, and Reconciliation in Canada. </i>By PauletteRegan.
Bibliographic record
Abstract
The Canadian settler state has enacted egregious practices of assimilation, dispossession, and genocide against First Nations, Inuit, and Metis peoples throughout its history. Running contrary to these practices are the prevailing narratives found in Canadian historical texts and settler national myths. In Unsettling the Settler, Paulette Regan addresses this contradiction by analyzing the "peacemaker" myth, which she suggests is deployed by the state to construct a history of settler innocence. In light of this, any acknowledgment of historical injustices committed by Canada, such as Indian Residential School policies, is iteratively couched in the promise of reconciliation. Seeking to navigate the complex terrain of reconciliation in Canada, Regan's text is an important contribution to settler studies in Canada. Unsettling encourages settlers to revisit the problematic appropriation of terms such as warrior and peacemaker that have been grossly misrepresented in settler myths as a way to reframe Indigenous approaches to reconciliation. In doing so, Regan demonstrates how attitudinal shifts may engender new material realities.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.022 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".