Nats’eji (healing): Examining patient and provider experiences with hospital-based Indigenous wellness services in Northwest Territories, Canada
Bibliographic record
Abstract
OBJECTIVE: This study aimed to examine how Indigenous patients and biomedical healthcare providers understand and experience the Indigenous wellness services at a hospital in the Northwest Territories. METHODS: The qualitative study (May 2018-June 2022) was overseen by a regional Indigenous Community Advisory Committee. Guided by Two-Eyed Seeing and post-colonial theory, the study employed a community-engaged research design, and included two strategies for data generation: (1) interviews with Indigenous Elders, patient advocates, biomedical healthcare providers, policy makers, and hospital administrators (n = 41), and (2) iterative sharing circles with Indigenous Elders (n = 4). Data from the interviews and first sharing circle were transcribed, thematically analyzed, and presented to the sharing circle Elders for validation. RESULTS: The study revealed three overarching and related themes: (1) Elders and patient advocates emphasized that while the Indigenous wellness services at the hospital play a pivotal role connecting patients with cultural supports, the hospital was still not effectively bringing Indigenous healing practices into hospital care; (2) participants identified that structural factors (i.e., policy and governance decisions) shaped patients' experiences with the wellness services; and (3) participants underscored that deeply rooted forces (i.e., racism, colonialism, and biomedical dominance) inhibit the integration of Indigenous healing practices. CONCLUSION: The findings extend understandings of hospital-based Indigenous wellness services by surfacing relationships between deeply rooted forces, organizational structures, and Indigenous patients' experiences. Altogether, they suggest that to advance care for Indigenous patients and improve the integration of Indigenous healing practices, a system-wide transformation is necessary, which includes Indigenous governance at the hospital and a recognition of the value of Indigenous healing practices.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".