Navigating Reconciliation in Occupational Therapy: Alberta Practitioners’ Experiences and Insights
Bibliographic record
Abstract
Background. The 2015 Truth and Reconciliation Commission of Canada issued Calls to Action, urging Canadians, including health-care providers, to address colonial harms and pursue reconciliation. Occupational therapists, guided by the Canadian Association of Occupational Therapist's Position Statement, are called to provide culturally safer care. However, little is known about how they engage in reconciliation in practice. Purpose. This study examines how occupational therapists integrate reconciliation into their practice and identifies influencing factors. Method. Reflexive thematic analysis was applied to data from semi-structured interviews with 11 occupational therapists. Discussions explored reconciliation efforts and related challenges. Findings. Occupational therapists foster reconciliation through building relationships with Indigenous communities and engaging in lifelong learning, such as accessing Indigenous knowledge and resources. Key barriers include gaps in foundational education and difficulties translating rhetoric into meaningful action. Participants stressed the need to deconstruct Western paradigms and adopt culturally responsive, non-Western approaches. Relationality, community engagement, and continuous learning emerged as central to reconciliation and culturally safer care. Conclusion. This study contributes to the national dialogue on truth and reconciliation by offering a foundation to understand truth and reconciliation in the context of occupational therapy. This may help to address systemic and anti-Indigenous racism in the profession.
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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 | 0.025 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.037 | 0.023 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.006 | 0.008 |
| 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".