Mentors, Colleagues, and Successful Health Science Faculty: Lessons from the Field
Bibliographic record
Abstract
Faculty members in medical and other professional schoolsare required to be fully functional soon after they beginemployment. Regardless of their experience, they areexpected to be productive in several areas related to clinicalservice and teaching. Most new faculty members are alsoexpected to engage in some form of research and to performleadership functions for their divisions, clinics, depart-ments, schools, and communities. These faculty roles andfunctions require significant skill levels that are expected tobe part of the new faculty member’s preparation.However, to be successful, new faculty also need tounderstand the social skills of their institution and theiracademic field. These skills involve much more than beingsociable. They include managing one’s career, finding andretaining productive colleagues, and understanding thenorms and values of academic medicine.
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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 | 0.026 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.009 |
| 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".