Supervisor Continuity or Co-Location
Bibliographic record
Abstract
PURPOSE: Changes to health care systems and working hours have fragmented residents' clinical experiences with potentially negative effects on their development as professionals. Investigation of off-site supervision, which has been implemented in isolated rural practice, could reveal important but less overt components of residency education. METHOD: Insights from sociocultural learning theory and work-based learning provided a theoretical framework. In 2011-2012, 16 family physicians in Australia and Canada were asked in-depth how they remotely supervised residents' work and learning, and for their reflections on this experience. The verbatim interview transcripts and researchers' memos formed the data set. Template analysis produced a description and interpretation of remote supervision. RESULTS: Thirteen Australian family physicians from five states and one territory, and three Canadians from one province, participated. The main themes were how remoteness changed the dynamics of care and supervision; the importance of ongoing, holistic, nonhierarchical, supportive supervisory relationships; and that residents learned "clinical courage" through responsibility for patients' care over time. Distance required supervisors to articulate and pass on their expertise to residents but made monitoring difficult. Supervisory continuity encouraged residents to build on past experiences and confront deficiencies. CONCLUSIONS: Remote supervision enabled residents to develop as clinicians and professionals. This questions the supremacy of co-location as an organizing principle for residency education. Future specialists may benefit from programs that give them ongoing and increasing responsibility for a group of patients and supportive continuity of supervision as residents.
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 | 0.012 |
| 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 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".