Sacred spaces in public places: religious and spiritual plurality in health care
Bibliographic record
Abstract
Several intriguing developments mark the role and expression of religion and spirituality in society in recent years. In what were deemed secular societies, flows of increased sacralization (variously referred to as 'new', 'alternative', 'emergent' and 'progressive' spiritualities) and resurgent globalizing religions (sometimes with fundamentalist expressions) are resulting in unprecedented plurality. These shifts are occurring in conjunction with increasing ethnic diversity associated with global migration, as well as other axes of difference within contemporary society. Democratic secular nations such as Canada are challenged to achieve social cohesion in the face of growing religious, spiritual and ethnic diversity. These challenges are evident in the high-paced, demanding arena of Health care. Here, religious and spiritual plurality enter in, sometimes resulting in conflict between medical services and patients' beliefs, other times provoking uncertainties on the part of healthcare professionals about what to do with their own religiously or spiritually grounded values and beliefs. In this paper, we present selected findings from a 3-year study that examined the negotiation of religious and spiritual pluralism in Health care. Our focus is on the themes of 'sacred' and 'place', exploring how the sacred - that which is attributed as special and set apart as it pertains to the divine, transcendence, God or higher power - takes form in social and material spaces in hospitals.
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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 | 0.010 | 0.013 |
| 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 | 0.028 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".