The View From the Top: Academic Emergency Department Chairs’ Perspectives on Education Scholarship
Bibliographic record
Abstract
Education scholarship continues to grow within emergency medicine (EM) and in academic medicine in general. Despite a growing interest, would-be education scholars often struggle to find adequate mentorship, research training, funding, and protected time to produce rigorous scholarship. The ways in which individual academic EM departments can support this mission remains an area in need of description. OBJECTIVES: We sought to describe academic EM department chairs' perceptions of education scholarship and facilitators and barriers to producing high-quality education scholarship. METHODS: We conducted a qualitative study using a grounded theory-derived approach. Participants were solicited directly, and semistructured interviews were conducted via telephone. Interviews were transcribed verbatim and were analyzed by three study investigators using a coding matrix. Discrepancies in coding were resolved via in depth discussion. RESULTS: We interviewed seven EM chairs from academic departments throughout North America (six in geographically diverse regions of the United States and one in western Canada). Chairs described education scholarship as lacking clearly defined and measurable outcomes, as well as methodologic rigor. They identified that education faculty within their departments need training and incentives to pursue scholarly work in a system that primarily expects teaching from educators. Chairs acknowledged a lack of access to education research expertise and mentorship within their own departments, but identified potential resources within their local medical schools and universities. They also voiced willingness to support career development opportunities and scholarly work among faculty seeking to perform education research. CONCLUSIONS: Academic EM chairs endorse a need for methodologic training, mentorship, and access to expertise specific to education scholarship. While such resources are often rare within academic EM departments, they may exist within local universities and schools of medicine. Academic EM chairs described themselves as willing and able to support faculty who wish to pursue this type of work.
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 | 0.037 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.024 |
| Scholarly communication | 0.025 | 0.013 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.007 | 0.014 |
| 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".