Bibliographic record
Abstract
A newly-structured Korean pharmacist license exam has been launched in 2015, reflecting upon the changes in the pharmacycurriculum from a 4 year program to a 6 year program in 2009. In order to provide new ideas to ensure that the new exam is oneof the most effective pharmacist evaluations that have taken place thus far, this study was done to compare the pharmacy examsin Korea and Canada. One of the major differences noted between the two countries' exams is that along with paper based MCQportion of the exam, Canada's exam also includes a performance-based section, known as OSCE, which the Korean PharmacyExam (KPE) does not have. Furthermore, with the MCQ portion of the exam, the Canadian exam asks about 300 questions, with 450minutes of test time allocated and taken during a period of two consecutive days, the KPE asks 350 questions, with 325 minutes oftest time allocated in one day. Although, similarly, many of the questions in both exams place emphasis on clinical or patient care,Canada's exam puts significantly more emphasis (50.5% of exam questions) on these types of questions than Korea (29.7% of examquestions). However, this percentage does not reflect the exact weight placed for the specific areas of knowledge it requires toanswer these questions, since the types of questions asked in this section in Canada could be placed in another section on theKPE. Canada's exam also has more questions (10% +150 questions for BC) on the topics of law and ethics compared to the KPE(5.7%). The reason for this may be that the Canadian society puts emphasis on the legal and ethical duties of pharmacists as aleader. However, since each country is unique in their social, economical, and cultural points of view, comparing the KPE to theCanadian licensing exam and applying these differences to the new KPE may not be appropriate. One last thing to consider is that,as WHO/FIP mentioned, in good pharmacy practice, continually updating and developing an appropriate pharmacy exam withconsideration of societal changes, is key to success in developing the scope of practice for current and future pharmacists.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.111 | 0.034 |
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".