Promoting Faculty Scholarship – An evaluation of a program for busy clinician-educators
Bibliographic record
Abstract
BACKGROUND: Clinician educators face barriers to scholarship including lack of time, insufficient skills, and access to mentoring. An urban department of family medicine implemented a federally funded Scholars Program to increase the participants' perceived confidence, knowledge and skills to conduct educational research. METHOD: A part-time faculty development model provided modest protected time for one year to busy clinician educators. Scholars focused on designing, implementing, and writing about a scholarly project. Scholars participated in skill seminars, cohort and individual meetings, an educational poster fair and an annual writing retreat with consultation from a visiting professor. We assessed the increases in the quantity and quality of peer reviewed education scholarship. Data included pre- and post-program self-assessed research skills and confidence and semi-structured interviews. Further, data were collected longitudinally through a survey conducted three years after program participation to assess continued involvement in educational scholarship, academic presentations and publications. RESULTS: Ten scholars completed the program. Scholars reported that protected time, coaching by a coordinator, peer mentoring, engagement of project leaders, and involvement of a visiting professor increased confidence and ability to apply research skills. Participation resulted in academic presentations and publications and new educational leadership positions for several of the participants. CONCLUSIONS: A faculty scholars program emphasizing multi-level mentoring and focused protected time can result in increased confidence, skills and scholarly outcomes at modest cost.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".