Faculty development using a virtual community of practice: Three‐year outcomes of the Academic Life in Emergency Medicine Faculty Incubator program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The Academic Life in Emergency Medicine (ALiEM) Faculty Incubator program is a longitudinal, 1-year, virtual faculty development program for early- and mid-career faculty members that crosses specialties and institutions. This study sought to evaluate the outcomes among 3 years of participants. METHODS: This cross-sectional survey study evaluated postcourse and 1-year outcomes from three graduated classes of the ALiEM Faculty Incubator program. The program evaluation survey was designed to collect outcomes across multiple Kirkpatrick levels using pre/post surveys and tracking of abstracts, publications, speaking opportunities, new leadership positions, and new curricula. RESULTS: Over 3 years, 89 clinician educators participated in the program. Of those, 59 (66%) completed the initial survey and 33 (37%) completed the 1-year survey. Participants reported a significant increase in knowledge (4.1/9.0 vs. 7.0/9.0). The number of abstracts, publications, and invited presentations significantly increased after course completion and continued postcourse. A total of 37 of 59 (62.7%) developed a new curriculum during the course and 19 of 33 (57.6%) developed another new curriculum after the course. A total of 29 of 59 (49.2%) began a new leadership position upon course completion with 15 of 33 (45.5%) beginning another new leadership position 1 year later. DISCUSSION: The ALiEM Faculty Incubator program demonstrated an increase in perceived knowledge and documented academic productivity among early- and mid-career medical educators.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it