The legality and appropriateness of keeping Korean Medical Licensing Examination items confidential: a comparative analysis and review of court rulings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the legality and appropriateness of keeping the multiple-choice question items of the Korean Medical Licensing Examination (KMLE) confidential. Through an analysis of cases from the United States, Canada, and Australia, where medical licensing exams are conducted using item banks and computer-based testing, we found that exam items are kept confidential to ensure fairness and prevent cheating. In Korea, the Korea Health Personnel Licensing Examination Institute (KHPLEI) has been disclosing KMLE questions despite concerns over exam integrity. Korean courts have consistently ruled that multiple-choice question items prepared by public institutions are non-public information under Article 9(1)(v) of the Korea Official Information Disclosure Act (KOIDA), which exempts disclosure if it significantly hinders the fairness of exams or research and development. The Constitutional Court of Korea has upheld this provision. Given the time and cost involved in developing high-quality items and the need to accurately assess examinees’ abilities, there are compelling reasons to keep KMLE items confidential. As a public institution responsible for selecting qualified medical practitioners, KHPLEI should establish its disclosure policy based on a balanced assessment of public interest, without influence from specific groups. We conclude that KMLE questions qualify as non-public information under KOIDA, and KHPLEI may choose to maintain their confidentiality to ensure exam fairness and efficiency.
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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 | 0.016 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it