Bibliographic record
Abstract
Abstract Canadians highly value their publically funded health care system and believe that quality end-of-life care is an imperative. Indeed, end-of-life care is consistent with the very values that resulted in the creation of a national health care system. However, the current system of end-of-life and hospice palliative care in Canada has been described as a patchwork of inadequate and inequitably available services. Access to services is influenced by the diseases Canadians die from, whether they live in a city or rural area, the province in which they reside, the nature of their health insurance plans, and their personal wealth.2 Only 5% to 10% of the 220,000 Canadians who die each year receive integrated and interdisciplinary palliative care. The estimated cost of dying in Canada is approximated at $ billion annually, with no performance indicators to suggest that resources are appropriately allocated. Recent federal reports are calling for federal action to address access to palliative care services, particularly in the home. The increased attention on end-of-life care and acknowledgment that services are inequitable challenge those responsible for health services delivery to develop initiatives and to address models of care for palliative care delivery.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.078 | 0.024 |
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".