Dermatologic Training and Practice in Canada: A Historical Overview
Bibliographic record
Abstract
The specialty of dermatology is constantly changing to meet the medical needs of our society. The discipline is in flux because of a variety of factors such as growing population needs, technological advancements, fiscal restraint, and demographic changes. As part of an in-depth review of the specialty, the Dermatology Working Group (DWG) for the Royal College of Physicians and Surgeons of Canada sought to determine whether the current training configuration is suitably preparing graduates to meet the societal health needs of dermatology patients. In this first of a 2-part series, the authors conducted comprehensive literature and historical reviews and a jurisdictional analysis to understand the current state of dermatology practice in Canada. Herein, they explore trends in the dermatology workforce, population needs, accessibility, and wait times, as well as issues in undergraduate and postgraduate medical education. In a subsequent publication, the DWG will utilize information gained from this historical analysis and jurisdictional review, stakeholder perspectives, and a national survey to shape the future of dermatology training in Canada.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.036 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".