Working with Parry sound area local Canadian First Nations to describe a good death and ensure cultural sensitivity at the end-of-life
Bibliographic record
Abstract
This study explores the culturally sensitive palliative and end-of-life care within First Nations communities in the Parry Sound area: Shawanaga, Wasauksing, and Moose Deer Point First Nations communities in Canada. The legacy of colonialism, particularly the Indian Act of 1876, has significantly disrupted Indigenous health practices, contributing to mistrust in Western healthcare systems. This research addresses gaps in culturally appropriate palliative and end-of-life care by identifying how First Nations communities define a "good death" and how Western healthcare providers can respect and integrate these traditions, particularly in rural and remote communities. Using a community-driven approach, three sharing sessions were conducted with 19 participants, exploring their insights into palliative and end-of-life care. Data analysis revealed five key themes: (1) Family members as primary caregivers, (2) Local healthcare providers support family in palliative and end-of-life care, (3) Make 'final journey' at home, (4) Community (the 'clan family') is involved in palliative and end-of-life care, and (5) Individual wishes for end-of-life care vary and should be followed by healthcare providers. These findings emphasize the role of family, community, and spiritual beliefs in shaping a "good death." The study calls for healthcare providers to incorporate cultural sensitivity, support home-based care, and collaborate with community leaders to bridge gaps between Western medicine and Indigenous traditions. Recommendations include fostering trust with healthcare providers, ensuring care aligns with cultural values, and enhancing collaboration between healthcare systems and Indigenous communities. This research contributes to improving palliative and end-of-life care for First Nations communities by promoting culturally safe, person-centred care 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".