Cultural Differences between American and Israeli Medical Students Regarding Their Perceptions of the Medical Profession and Satisfaction with Studies
Bibliographic record
Abstract
Background: Cultural differences have been discussed as a potential factor influencing students' perception and motivation towards their studies. At the Sackler Faculty of Medicine, Tel-Aviv University, two separate programs coexist for American and Israeli medical students. Both are taught at the same sites and by the same faculty, thus enabling cultural comparisons. Our aim was to examine the differences of two medical student groups, American and Israeli, regarding their satisfaction with studies, view of the educational workload, and their perceptions of physician characteristics. Methods: During the academic year 2007-2008 we administered an anonymous questionnaire to the two groups immediately after their first clinical clerkship in internal medicine. The response rate was 82% (90 out of 110) for the Israelis and 93% (53 out of 57) for the Americans.Results: Americans, compared to the Israelis, are significantly more satisfied with their medical studies, consider fewer alternatives to future careers in clinical medicine, feel less of a workload, and hold a more positive opinion of physician characteristics.Conclusions: Cultural differences affect students' perception of their studies, mentors and future careers. Medical educators should be sensitive to the effects of students' background which influence academic and professional attitudes and find ways to strengthen their commitment to the profession.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".