Decolonizing a Settler Colonial State: How Canada and the United States Have Approached Investigations Into Indigenous Boarding and Residential Schools
Bibliographic record
Abstract
Indigenous boarding and residential schools were in use for over 100 years in both Canada and the United States. Grown from numerous policies aimed at assimilation, dispossession, and genocide of the Indigenous peoples of North America, these residential schools had a particular aim: to wipe away all cultural and familial ties of every individual and to replace them with beliefs and values of white settlers. Though the schools are no longer in operation, their legacy of erasure and pain continues to affect survivors, their descendants, and Indigenous communities across both nations. This thesis looks at what the federal governments of Canada and the United States have done about residential schools since their operation. Specifically, this thesis analyzes federal investigation, reconciliation, and reparations efforts regarding Indigenous boarding and residential schools. Using the methodology of content analysis, as well as the conceptual frameworks of decolonization and decoloniality, this thesis seeks to answer the following research questions: (1) to what extent have reparations efforts made by Canada and the U.S. furthered a broader agenda of decolonization; and (2) how and why has Canada made more progress in investigating boarding schools, and does this necessarily mean they have come closer to decolonization? The ultimate goal is to determine whether either federal government has made meaningful steps towards interrogating their past policies towards Indigenous peoples, and whether that has led the United States or Canada to begin down a decolonial path.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.062 | 0.041 |
| Scholarly communication | 0.017 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".