Education in long-term care for family medicine residents: description of an integrated program.
Bibliographic record
Abstract
PROBLEM ADDRESSED: Family medicine residents require more exposure to all aspects of care of the elderly in the community, including care in long-term care (LTC) homes. OBJECTIVE OF PROGRAM: To provide a framework for the development of integrated LTC rotations in family medicine programs. PROGRAM DESCRIPTION: Clear objectives for residents and clinical preceptors provided the foundation for the program. Rotations of 4 half days per year in LTC homes were integrated into core family medicine blocks. Residents worked with family physician preceptors providing LTC in the community. Teaching was case based and aligned with the core competencies set out in the CanMEDS (Canadian Medical Directives for Specialists) framework for medical education. The program was strongly supported by the university's administration, clinical preceptors in the community, and LTC homes. CONCLUSION: All the residents rated their LTC rotations as useful or extremely useful in preparing them to provide LTC in their future practices. Long-term care homes realized that investing in training medical residents in LTC could help improve care of the elderly 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".