Expertise, Time, Money, Mentoring, and Reward: Systemic Barriers That Limit Education Researcher Productivity—Proceedings From the AAMC GEA Workshop
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
BACKGROUND: To further evolve in an evidence-based fashion, medical education needs to develop and evaluate new practices for teaching, learning, and assessment. However, educators face barriers in designing, conducting, and publishing education research. OBJECTIVE: To explore the barriers medical educators face in formulating, conducting, and publishing high-quality medical education research, and to identify strategies for overcoming them. METHODS: A consensus workshop was held November 5, 2013, at the Association of American Medical Colleges annual meeting. A working group of education research experts and educators completed a preconference literature review focusing on barriers to education research. During the workshop, consensus-based and small group techniques were used to refine the broad themes into content categories. Attendees then ranked the most important barriers and strategies for overcoming them with the highest potential impact. RESULTS: Barriers participants faced in conducting quality education research included lack of (1) expertise, (2) time, (3) funding, (4) mentorship, and (5) reward. The strategy considered most effective in overcoming these barriers involved building communities of education researchers for collaboration and networking, and advocating for education researchers' interests. Other suggestions included trying to secure increased funding opportunities, developing mentoring programs, and encouraging mechanisms to ensure protected time. CONCLUSIONS: Barriers to education research productivity clearly exist. Many appear to result from feelings of isolation that may be overcome with systemic efforts to develop and enable communities of practice across institutions. Finally, the theme of "reward" is novel and complex and may have implications for education research productivity.
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 | 0.005 | 0.031 |
| 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