American Journal of Pharmaceutical Education 2003; 67 (3) Article 76. INSTRUCTIONAL DESIGN AND ASSESSMENT Development and Validation Processes for an Objective Structured Clinical Examination (OSCE) for Entry-to-Practice Certification in Pharmacy: The Can
Bibliographic record
Abstract
Objectives. An objective structured clinical examination (OSCE) was developed and validated as an addition to the entry-to-practice examination for pharmacists that previously consisted of both a multiple-choice, case-based written test of clinical knowledge and a performance assessment. Methods. Designing the OSCE for entry-to-practice certification of pharmacists in Canada required extensive consultation with stakeholders, development of an examination blueprint outlining competencies to be assessed, careful development and validation of multiple OSCE stations with tasks linked to the blueprint, development of assessment instruments, field testing of stations, development and validation of standard-setting procedures, and protocols for data collection and analysis. Results. The examination was field tested, finalized, and first delivered in May 2001. Preliminary analysis of results indicated the development and validation processes were successful in producing an OSCE model that is reliable with valid outcomes, defensible, and feasible. Conclusion. The Pharmacy Examining Board of Canada’s Qualifying Examination (Part II – OSCE) represents the first time that a multi-site national licensing exam for entry-level practitioners in pharmacy has incorporated an objective structured clinical examination component. Together, the written and OSCE exams provide a broad assessment of competency, to ensure entry-level practitioners meet standards of practice for the protection of the public.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.015 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.006 |
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".