Teaching Dermatology to Canadian Undergraduate Medical Students
Bibliographic record
Abstract
BACKGROUND: The Canadian dermatology undergraduate curriculum was reviewed in 1983, 1987, and 1996. All surveys revealed the limited amount of time dedicated to dermatology in the undergraduate curriculum. OBJECTIVE: This survey was designed to obtain current information regarding undergraduate dermatology teaching in Canadian medical schools. METHODS: A survey was sent electronically to all undergraduate dermatology curriculum coordinators at each of the 17 Canadian medical schools. RESULTS: Between 1996 and 2008, the average number of hours of dermatology teaching has increased by 7 hours to 20.5 ± 17.2 hours. Again, most of the teaching is performed in the preclinical years. The majority of schools would like to have more time dedicated to dermatology teaching; however, many schools cited a restriction in the number of dermatology faculty members, with an average of 7.8 ± 7 dermatologists, as a barrier to education delivery. CONCLUSION: It is important to have dermatology included throughout the undergraduate medical curriculum because most dermatologic problems are seen by nondermatologists. Respondents at each school believed that there may be value in moving toward a national strategy for dermatology curriculum changes, and this can ensure both uniformity and consistency within 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".