In Search of the Truth: Uncovering Nursing’s Involvement in Colonial Harms and Assimilative Policies Five Years Post Truth and Reconciliation Commission
Bibliographic record
Abstract
The year 2020 marks five years since the Truth and Reconciliation Commission (TRC) of Canada released its Calls to Action, directing nursing to take action on both “truth” and “reconciliation.” The aim of this article is to examine how nurses have responded to the TRC’s call for truth in uncovering nursing’s involvement in past and present colonial harms that continue to negatively impact Indigenous people. A narrative review was used to broadly examine nurses’ responses to uncovering nursing’s complicity in five colonial harms: Indian hospitals, Indian Residential Schools, child apprehension, Missing and Murdered Indigenous Women and Girls (MMIWG), and forced sterilization. The paucity of results during the post-TRC period demonstrates a lack of scholarship in uncovering the truth of nursing’s complicity in these systems. Based on findings, we explore two potential barriers in undertaking this work in nursing, including a challenge to the image of nursing and anti-Indigenous racism.
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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 | 0.027 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.031 | 0.036 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| 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".