Barriers and Strategies to Engaging Our Community-Based Preceptors
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
ISSUE: This article, from the "To the Point" series that is prepared by the Association of Professors of Gynecology and Obstetrics Undergraduate Medical Education Committee, is a review of commonly cited barriers to recruiting and retaining community-based preceptors in undergraduate medical education and potential strategies to overcome them. EVIDENCE: Community-based preceptors have traditionally served as volunteer, nonsalaried faculty, with academic institutions relying on intrinsic teaching rewards to sustain this model. However, increasing numbers of learners, the burdens of incorporating the electronic medical record in practice, and increasing demands for clinical productivity are making recruitment and retention of community-based preceptors more challenging. IMPLICATIONS: General challenges to engaging preceptors, as well as those unique to women's health, are discussed. Potential solutions are reviewed, including alternative recruitment strategies, faculty development to emphasize efficient teaching practices in the ambulatory setting, offers of online educational resources, and opportunities to incorporate students in value-added roles. Through examples cited in this review, clerkship directors and medical school administrators should have a solid foundation to actively engage their community-based preceptors.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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