Bibliographic record
Abstract
Canada's high level of spending on healthcare and lagging performance are leading policy makers and system managers to explore the concept of value. The concept, applied to healthcare, is appearing in medical media and policy documents with increasing frequency and is being used to describe patients' outcomes vis-à-vis the costs of achieving the outcomes. A uniquely Canadian interpretation of value is needed that recognizes that patients', providers' and society's perspectives of the value of the same health service or medical technology differ. This issue of Healthcare Papers presents complementary articles whose authors explore options for improving the value from public spending on healthcare. Commonalities among the articles indicate that improving value from healthcare should focus on understanding what matters to patients and their caregivers and measuring health and health outcomes and that changes in financial incentives are overdue to support a higher degree of integration between providers and their organizations.
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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".