Bibliographic record
Abstract
Abstract When Cicely Saunders set up St. Christopher’s Hospice in 1967, she created whole-person care for patients who were dying and a model for the transformation of healthcare. This model of care, which combined healing and curing, has key aspects that needed to be addressed if the full potential of palliative medicine is to be realized. (1) Healing is a complex powerful process that is unpredictable and difficult to measure. (2) Curing is a radically different process, the impact of which is easier to quantify. These two processes synergize, but, in the tension between them, curing tends to be favored over healing. (3) The efficiency promoted by most healthcare institutions focuses primarily on the measurable actions and outcomes related to curing, further decreasing the time and attention to healing. (4) The authors have taught an approach to care based on mindfulness and congruence (mindful clinical congruence) to all medical students in all 4 years at McGill University that promotes a way of relating to patients that makes space for both healing and curing. (5) For this approach to succeed, both in palliative care and healthcare generally, will require a new kind of medical professionalism, where healing is seen as the bedrock of practice and curing as the context in which healing takes place. Communities of trust will be necessary for this transformation, which the authors believe will benefit both professional caregivers and the patients to whom they deliver care.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".