Designing a First Year Integrated Course to Meet the Mission & Values of a New Medical School
Bibliographic record
Abstract
It is exciting to design a new medical school curriculum because you have a table rasa or clean slate with which to work. The design of the curriculum has to fit within the culture that is being built in the medical school. In constructing the curriculum, it is important to evaluate the mission and values that will be the guiding principles. The Commonwealth Medical College's (TCMC) mission involves serving “society using a community‐based, patient‐centered, interprofessional and evidenced‐based model of education” and “utilizes innovative techniques.” Two of the three major first year courses integrate the basic sciences and particularly the anatomical sciences within the spiral curriculum. Gross anatomy, histology, embryology, radiological anatomy, clinical anatomy and physiology are components of the Human Structure and Function (HSF) course that runs 17 weeks. Pathology, microbiology and pharmacology play a role in HSF but are not studied to the same depth as in the second year. The other first year course is Brain, Mind and Behaviour (BMB), which follows a patient presentation approach, used by the University of Calgary. BMB will initiate students to applying clinical reasoning to their learning and integrating all basic sciences. Much enthusiasm and support for our curriculum comes from our community clinical faculty, who have volunteered to participate in the teaching and learning program at TCMC.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".