The Need for Health Care Principles
Bibliographic record
Abstract
Community health-improvement collaboratives, which represent both health care consumers and health care providers in efforts to improve health care systems at the local level, are becoming a major force for improving health care systems throughout the world (1-3). However, many authors have argued that members of local collaboratives must unite around shared principles in order for their efforts to be successful (4-7). This article describes the development of a set of ethical principles, based on essential health needs, that can serve as a common foundation for collaboratives attempting to improve local health care systems. Many nations have already organized their health care systems according to principles chosen to help them best meet the needs of consumers. For example, Canada based its health care system on the principles of comprehensiveness, universality, portability, accessibility, and public administration (8). Similarly, the proposed Clinton health plan (9) and Newt Gingrich’s recommendations for transforming the U.S. health care system (10) both placed basic ethical principles and fundamental consumer health interests at the forefront.
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 | 0.083 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.076 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.025 | 0.051 |
| Insufficient payload (model declined to judge) | 0.009 | 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".