Physician assistants: education, practice and global interest
Bibliographic record
Abstract
BACKGROUND: In the United States, the physician assistant (PA) model has proven to be a cost-effective way to train quality primary care providers with a high degree of acceptance of the PA role by patients and other healthcare providers. AIM: Discuss PA model as it pertains to other countries. METHODS: Review of relevant literature related to physician assistant education, practice and global interest. RESULTS: Several countries including the United Kingdom, Scotland, Canada, The Netherlands, Taiwan, South Africa and Ghana are exploring or re-exploring the concept of the physician assistant as a way to quickly and efficiently train and employ autonomous and flexible health workers to address their nation's healthcare needs. CONCLUSIONS: Physician assistant education is efficient and flexible and the PA model can be easily adapted to the specific health system needs of other nations. In addition, many PA programs have affiliation agreements with institutions outside of the United States to host PA students for clinical rotations and there is an ever-growing interest by students in international rotations. The Physician Assistant Education Association along with the American Academy of Physician Assistants is actively involved with sharing information about the PA profession with other countries.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".