The Responsibilities and Activities of Internal Medicine Clerkship Directors
Bibliographic record
Abstract
PURPOSE: To characterize the responsibilities, activities, and scholarly productivity of internal medicine clerkship directors (CDs). METHODS: In 1999, internal medicine CDs from 122 U.S. medical schools and one Canadian medical school were surveyed. The instrument asked about the CDs' demo-graphics, workloads, clerkship characteristics, and scholarly productivity. RESULTS: The response rate was 89%; 72% of the respondents were men. Mean age was 45 years, mean time as CD was 6.5 years, and 58% of the CDs had completed fellowship training. The CDs spent 28% of their professional time on the clerkship, three half days weekly in clinic, and three months on inpatient services. The CDs had published a mean of 2.2 (range 0-20) articles and received a mean of 0.7 (range 0-4) grants. Similar factors were associated with publishing articles and receiving grants; gender (men), < or = three clinic half days weekly, fellowship training, having a faculty development program, teaching other courses, and discussing expectations with their department chairs. In a multivariate analysis, fellowship training, clinic half days, teaching other courses, and discussing expectations explained 22% of the variance for papers published. For grants received, a model with gender, clinic half days, a faculty development program, discussing expectations, and teaching other courses explained 35% of the variance. CONCLUSIONS: An internal medicine CD invests significant effort administering the clerkship and contributing to clinical and educational activities. The factors associated with successful scholarship may be useful for fostering CDs' academic careers.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".