Firsthand Experience in Graduating Three Cohorts of Forensic Pathologists Trained With Competency by Design (CBD) Curriculum
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The University of Toronto experienced graduating three cohorts of forensic pathologists trained with Competency by Design (CBD) curriculum. We achieved this as a result of multiyear development of Entrustable Professional Activities (EPAs), Required Training Experience (RTEs), and Specialty Competency Requirements (SCRs) by the Royal College of Physicians and Surgeons of Canada's Forensic Pathology Speciality Committee, the Ontario Forensic Pathology Service, and the University of Toronto. METHOD: Our academic year is comprised of 13 blocks. We divided the 13-block period into 4 stages to map all the EPAs and RTEs. The first stage, Transition to Discipline, is 1 block, the second stage, Foundation of Discipline, consists of 3 blocks; the third stage, Core of Discipline, consists of 6 blocks, and the final fourth stage, Transition to Practice, consists of 3 blocks. Board-certified faculty members in Forensic Pathology with more than five years of experience supervised the trainees. We graduated 5 Canadian and 4 international trainees at the end of the third cycle of CBD-based training program. CONCLUSION: Using the Royal College Speciality Committee blueprint, the University of Toronto started in 2016 planning the CBD curriculum in the forensic pathology training program. By the end of June 2021, we graduated nine trainees from our CBD-based Forensic Pathology training program. We are training the fourth cohort, and they will be graduating at the end of June 2022. This article aims to share our firsthand experiencing in CBD training in forensic pathology.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it