Current Status of the Resident Education Program and the Necessity of a General Competency Curriculum
Bibliographic record
Abstract
In order to adapt to the rapidly changing medical environment, it is important to advance not only the basic medical education in medical schools but also that of residents. The quality of the training environment and educational goals for residency must also be improved for specialists. Although each institute including internal medicine, general surgery, family medicine, etc., strives to standardize, sets educational goals, and develops content to train capable specialists, the education programs focus on special techniques and competency of medical care for patients. The training environment of each residency program is different in each trainee hospital, and hospitals are making an effort to set education goals for the residents and improve their education programs. In Korea, there is no common core education program for residents, while in the United States, the Accreditation Council for Graduate Medical Education is responsible for the development and evaluation of a standardized curriculum for residents, and in Canada, CanMEDs presents a basic curriculum to help residents develop competency. Fully capable specialists have more than just clinical competency; they also need a wide range of abilities including professionalism, leadership, communication, cooperation, in addition to taking part in continuous professional development/continuing medical education activities. We need to provide a core curriculum for residency to demonstrate attention to and knowledge about health problems of the community.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".