Bases of Person Centered Medical Education to Enhance Health Systems Worldwide
Bibliographic record
Abstract
Medicine is at the heart of healthcare. Healthcare systems have contributed to increasing the life expectancy and the wellbeing of millions of people worldwide during the 20th century [1] and they represent an asset of utmost importance in achieving fairness in accessing health-related prevention, promotion and recovery from illness [2]. Thus one of the driving purposes of medical education must be to enhance the performance of health systems for meeting the needs of patients and populations in an equitable and efficient way. A crucial factor in this endeavor will be the successful adaptation of professional education for local and national leadership in workforce teams that are capable of extending reach to all people. The purpose of this paper is to explore a deeper understanding that a person centered approach is essential as to how this can be achieved.Health is about people. The goal of physicians and all health professionals, irrespective of nationality and specialty is to share a common global vision for the future. [3] In this, all health professionals in all countries should be educated to gather knowledge, and to engage in critical reasoning and practice to high ethical standards so that they are competent to participate in person-centered and people-centered health systems as members of locally responsive and globally connected teams. The ultimate vision must be to assure universal coverage of high-quality comprehensive services that are essential to advancing opportunity for health equity within and between countries [4]. The aspiration for better health commonly shared will resonate with aspiring young professionals who seek value and meaning in their work.
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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 | 0.027 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".