Medical School Performance as Measured by GPA: What Can it Predict?
Bibliographic record
Abstract
Abstract Introduction Medical graduates' performance has been an area of interest for medical educators internationally. The objectivity of such measures has made it an essential part in evaluation of applicants. Objectives The aim of our study is to examine the prognostic value of medical school graduation GPA in relation to post-graduation achievements and success. Methods We used an online questionnaire sent to Kuwait university's graduates, whether directly face to face, by messages, or phone calls. The electronic questionnaire consisted of three major area, sociodemographic, medical school GPA, and academic or clinical achievements. The results have been statistically analyzed using satisfaction with life, satisfaction with career, and career progress as dependent variables. Results A total of 552 physicians who graduated from 1983 to 2017 took part in this study. The mean age was 33.31 ± 8.39 years. The highest percentage of participant (33%) were specialized in internal medicine. A higher GPA was found to be associated with pursuing postgraduate clinical fellowship, earning higher monthly income, higher career progress score, and scoring higher personal satisfaction with progress and life scores. Higher GPA was not associated with being a faculty member, pursuing post graduate academic studies like master's degree and doctor of philosophy, practicing internationally, or having publications. Gender was not associated with doing a fellowship or practicing internationally. Conclusion Medical school performance, measured by GPA, might predict higher career progress, having higher monthly income, and satisfaction. However, it is not necessarily prognostic for pursuing postgraduate academic degrees, practicing internationally, or having research publications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.009 |
| Insufficient payload (model declined to judge) | 0.072 | 0.002 |
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; both teacher heads agree on what is shown here.
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".