Bibliographic record
Abstract
The first hospice devoted to what has come to be known as palliative care was founded in South-East London in 1967 by Cicely Saunders. In its wake, many similar wards were created around the world, as for instance in Montreal. Already as a teenager, Cicely Saunders was moved by the suffering of others. Her encounter with David Tasma, a Polish-Jewish refugee and Warsaw ghetto survivor who was dying far away from his family proved inspirational. They had a mutually enriching relationship. Cicely’s medical dedication to patient care originated with David. She introduced the now well known mantra : « care rather than cure ». Many reforms were needed, and she had the opportunity to implement them when she established St Christopher’s Hospice. Two major texts outline the blueprints of her actions : The Need then The Scheme. Cicely set out with great determination to build the first hospice where a pluri-disciplinary team would work toward relieving total pain. Their motto was : « be watchful ! ». Cicely worked actively toward the establishment of other hospices. She was also involved in the debate over euthanasia in the mid seventies arguing that when pain is controlled effectively euthanasia is prima facie not needed. The danger of a possible legalization is that terminally ill patients may interpret a right as a duty.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.038 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".