Understanding community family medicine preceptors’ involvement in educational scholarship: perceptions, influencing factors and promising areas for action
Bibliographic record
Abstract
BACKGROUND: Residency training is increasingly occurring in community settings. The opportunity for community-based scholarship is untapped and substantial. We explored Community Family Medicine Preceptors' understanding of Educational Scholarship (ES), looked at barriers and enablers to ES, and identified opportunities to promote the growth of ES in this setting. METHODS: We conducted semi-structured interviews with fifteen purposively chosen community-based Family Medicine preceptors in a distributed Canadian family medicine program. RESULTS: Community Family Medicine Preceptors strongly self-identify as clinical teachers. They are not well acquainted with the definition of ES, but recognize themselves as scholars. Community Family Medicine Preceptors recognize ES has significant value to themselves, their patients, communities, and learners. Most Community Family Medicine Preceptors were interested and willing to invest in ES, but lack of time and scarcity of primary care research experience were seen as barriers. Research process support and a connection to the academic center were considered enablers. Opportunities to promote the growth of ES include recognition that there are fundamental differences between community and academic sites, the development of a mentorship program, and a process to encourage engagement. CONCLUSIONS: Community Family Medicine Preceptors identify foremost as clinician teachers. They are engaged in and recognize the value of ES to their professional community at large and to their patients and learners. There is a growing commitment to the development of ES in the community.
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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 | 0.020 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".