Completing the Circle: Elders Speak about End-Of-Life Care with Aboriginal Families in Canada
Bibliographic record
Abstract
In this article, we share words spoken by Aboriginal elders from Saskatchewan, Canada, in response to the research question, "What would you like non-Aboriginal health care providers to know when providing end-of-life care for Aboriginal families?" Our purpose in publishing these results in a written format is to place information shared by oral tradition in an academic context and to make the information accessible to other researchers. Recent theoretical work in the areas of death and dying suggests that cultural beliefs and practices are particularly influential at the end of life; however, little work describing the traditional beliefs and practices of Aboriginal peoples in Canada exists to guide culturally appropriate end-of-life care delivery. Purposive sampling procedures were used to recruit five elders from culturally diverse First Nations in southern Saskatchewan. Key informant Aboriginal elder participants were videotaped by two Aboriginal research assistants, who approached the elders at powwows. Narrative analysis of the key informant interview transcripts was conducted to identify key concepts and emerging narrative themes describing culturally appropriate end-of-life health care for Aboriginal families. Six themes were identified to organize the data into a coherent narrative: realization; gathering of community; care and comfort/transition; moments after death; grief, wake, funeral; and messages to health care providers. These themes told the story of the dying person's journey and highlighted important messages from elders to non-Aboriginal health care providers.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.042 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".