Pharmacists teaching in family medicine residency programs: National survey.
Bibliographic record
Abstract
OBJECTIVE: To determine the percentage of family medicine residency programs that have pharmacists directly involved in teaching residents, the types and extent of teaching provided by pharmacists in family medicine residency programs, and the primary source of funding for the pharmacists. DESIGN: Web-based survey. SETTING: One hundred fifty-eight resident training sites within the 17 family medicine residency programs in Canada. PARTICIPANTS: One hundred residency program directors who were responsible for overseeing the training sites within the residency programs were contacted to determine the percentage of training sites in which pharmacists were directly involved in teaching. Pharmacists who were identified by the residency directors were invited to participate in the Web-based survey. MAIN OUTCOME MEASURES: The percentage of training sites for family medicine residency that have pharmacists directly involved in teaching residents. The types and the extent of teaching performed by the pharmacists who teach in the residency programs. The primary source of funding that supports the pharmacists' salaries. RESULTS: More than a quarter (25.3%) of family medicine residency training sites include direct involvement of pharmacist teachers. Pharmacist teachers reported that they spend a substantial amount of their time teaching residents using a range of teaching modalities and topics, but have no formal pharmacotherapy curriculums. Nearly a quarter (22.6%) of the pharmacists reported that their salaries were primarily funded by the residency programs. CONCLUSION: Pharmacists have a role in training family medicine residents. This is a good opportunity for family medicine residents to learn about issues related to pharmacotherapy; however, the role of pharmacists as educators might be optimized if standardized teaching methods, curriculums, and evaluation plans were in place.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".