Integrating Religious and Cultural Supports into Quality Care in the Last Stages of Life in Ontario
Bibliographic record
Abstract
The last stages of life – and particularly end-of-life care, palliative care, and medical assistance in dying – have emerged as key health care issues of importance to a broad and growing diversity of multicultural Canadians. This paper presents a snapshot of how faith and cultural supports are an essential aspect of quality care in the last stages of life in Ontario. The paper begins by defining key terms and distinctions in the “last stages of life” and as between various beliefs and practices. The paper then overviews key legislative and professional regulatory frameworks, as well as various best practice models and existing community-based programs. The authors then present qualitative findings based on interviews with 17 faith leaders and health practitioners from the Greater Toronto Area and Southwestern Ontario. This is additionally supplemented by research conducted into the palliative and pastoral services available to patients at 19 of the busiest hospitals in Ontario (as identified by data obtained from Canadian Institute for Health Information). The paper concludes with recommendations to enhance the quality of care for a diverse, multicultural population contending with the last stages of life.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".