A Time for Action on Health Inequities: Foundations of the 2014 Geneva Declaration on Person- and People-centered Integrated Health Care for All
Bibliographic record
Abstract
Global inequalities contribute to marked disparities in health and wellness of human populations. Many opportunities now exist to provide health care to all people in a person- and people-centered way that is effective, equitable, and sustainable. We review these opportunities and the scientific, historical, and philosophical considerations that form the basis for the International College of Person-centered Medicine’s 2014 Geneva Declaration onPerson- and People-centered Integrated Health Care for All. Using consistent time-series data, we critically examine examples of universal healthcare systems in Chile, Spain, and Cuba. In a person-centered approach to public health, people are recognized to have intrinsic dignity and are treated with respect to encourage their developing health and happiness. A person-centered approach supports the freedom and the responsibility to develop one’s life in ways that are personally meaningful and that are respectful of others and the environment in which we live together. Evidence suggests that health care organizations function well when they operate in a person-and people-centered way because that stimulates better coordination, cooperation, and social trust. Health care coverage must be integrated at several interconnected levels in order to be effective, efficient, and fair. To reduce the burden of disease, integration is needed between the people seeking and delivering care, within the social network of each person, across the trajectory of each person’s life, among primary caregivers and specialists, and across multiple sectors of society. For integration to succeed across all these levels, it must foster common values and a shared vision of the future.
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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 | 0.085 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.092 |
| Scholarly communication | 0.023 | 0.025 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.029 | 0.059 |
| Insufficient payload (model declined to judge) | 0.005 | 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".