The relationship between pharmacy licensing policies on clinical training (CT) and success rates for international pharmacists (IPs) within Canada, United Kingdom, and the United States: A comparative policy analysis
Bibliographic record
Abstract
Introduction: In October 2018, the Pharmacy Examining Board of Canada released a report showing that only 41.1% of international pharmacists pass the Pharmacy Qualifying Examination, compared to 91% of Canadian graduates. When compared to the United Kingdom and United States, Canada has the lowest success rates for the integration of international pharmacists. Aim: This study aims to address two questions: What are the professional pharmacy policies governing the clinical training resources for international pharmacists within their host country? What can Canada learn from other Western countries to facilitate the integration of international pharmacists? Method: A comparative policy analysis was used to draw comparisons between Canada’s regulatory policies governing the pharmacy license to other similar models in the United Kingdom and United States. Results: Upon examining current integration systems in these countries, differences in training period requirements and competencies became apparent. Therefore, the findings suggest that Canadian stakeholders can learn from other models’ legislation, structure, and clinical outcome prospects.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".