From Medical School Application to Being Family Physician: Education And Career Journey of Medical Students
Bibliographic record
Abstract
Aim: Medical schools in Turkey offer six-years-long undergraduate medical education. Most of them divide these six years into three period: The pre-clinical period is the first three years, the clinical period is the next two years, and the last year is practice-oriented internship. Education of family medicine specialty lasts three years. The aim of this study is to present; terms and processes of medical school applications, time structure of undergraduate medical education, terms of application to specialty education, and duration of family medicine specialty education in European Union (EU), United States of America (USA), Australia, United Kingdom, China, Japan, Canada, Russia, Singapore.Method: To access the information about processes of the medical education in foreign countries, a literature search was conducted between 03.10.2019-06.01.2020. Pubmed, Scopus and Google Scholar have been screened by using keywords. In addition to this, websites of some organizator institutions on medical education and healthcare as well as websites of some medical schools have been accessed.Results: In general, undergraduate medical education lasts 3-6 years. These years are divided into two parts; pre-clinical and clinical periods. To make application to medical school in USA and Canada, students have to be gotten a bachelor degree. Some countries require students 1-3 years of internship after graduation. Students have to sign “return of service” agreement in some specialty areas in Canada. Commonly, family medicine specialty education lasts 3 years.Conclusion: The phases of which students should pass from medical school application to being family physicians are different in every country. In spite of the differences, there are similar parts. Educational features and primary care career pathways in foreign countries should be investigated to adopt their positive sides for our country. Thus, our primary care physicians in future would provide better service to the community.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".