Bibliographic record
Abstract
Abstract The revised edition of Crossing Over is a book of stories—narratives of giving and receiving palliative care in the context of end of life. It is not a textbook that portrays ideal palliative care or that prescribes specific management techniques. Instead, it presents stories of actual patients and families who have experienced terminal illness with the support of hospice or palliative care teams. The narratives are derived from a three-year, qualitative, ethnographic study of the experiences of patients, families, and caregivers. Since the first edition of Crossing Over appeared, changes have occurred in healthcare and in society at large that have altered the environment in which people give and receive palliative care, including effects of the COVID-19 pandemic, the opioid crisis, changes in social welfare policy, the rise of the internet, the evolution of palliative care as a field, increased emphasis on advance care planning, and, in some jurisdictions (including all of Canada), legalization of medical aid in dying. The Authors’ Comments following each narrative pinpoint specific decisions and choices of patients, families, and clinicians where today’s changed context may be particularly relevant.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.016 |
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".