Fostering interest in family medicine. Focusing on patient-physician relationships.
Bibliographic record
Abstract
Over the past year, Residents’ Pages have presented several articles devoted to career choice. As family medicine (FM) residents, we often interact with medical students. Many of us are likely to become clinical teachers in the near future. Most of us are concerned with the recent Canadian Resident Matching Service (CaRMS) statistics and impending exacerbation of family physician shortages in Canada. Consequently, I and my colleagues have found ourselves spouting the virtues of family medicine: clinical variety, freedom to choose where and how one practises medicine, and many other joys and challenges. It is diffi cult, however, to connect our experiences as residents to those we had as medical students. During 2 years of residency, we have time to establish relationships with “our” clinic patients to provide continuity of care. As medical students, we were 4week guests in another physician’s practice, dependent on chart notes to provide an introduction, and not infrequently faced with patients who were resentful at seeing us before “their” doctors. Unfortunately, one of the most rewarding aspects of FM, continuity of care, disappeared from patient encounters in medical school. Is this loss avoidable? In this month’s Residents’ Page, Dr Wong offers his perspective on undergraduate medical education and the importance of physician-patient relationships in teaching FM, along with strategies to improve students’ clinical encounters. Dr Malkin is in her second year of residency in family medicine at McGill University in Montreal, Que, and is a member of the Editorial Advisory Board of Canadian Family Physician.
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.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".