Bibliographic record
Abstract
BACKGROUND: The assessment of a practising physician's performance may be conducted for various reasons, including licensure. In response to a request from the College of Physicians and Surgeons of Manitoba (CPSM), the Division of Continuing Professional Development in the Faculty of Medicine, University of Manitoba, has established a practice-based assessment programme - the Manitoba Practice Assessment Program (MPAP) - as the College needed a method to evaluate the competence and performance of physicians on the conditional register. CONTEXT: Using a multifaceted approach and CanMEDS as a guiding framework, a variety of practice-based assessment surveys and tools were developed and piloted. Because of the challenge of collating data, the MPAP team needed a computerised solution to manage the data and assessment process. INNOVATION: Over a 2-year period, a customised web-based forms and information management system was designed, developed, tested and implemented. The secure and robust system allows the MPAP team to create assessment surveys and tools in which each item is mapped to Canadian Medical Education Directives for Specialists (CanMEDS) roles and competencies. Reports can be auto-generated, summarising a physician's performance on specific competencies and roles. Overall, the system allows the MPAP team to effectively manage all aspects of the assessment programme. IMPLICATIONS: Throughout all stages of design to implementation, a variety of lessons were learned that can be shared with those considering building their own customised web-based system. The key to success is active involvement in all stages of the process!
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 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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".