Specialty resident perceptions of the impact of a distributed education model on practice location intentions
Bibliographic record
Abstract
OBJECTIVES: There is an increased focus internationally on the social mandate of postgraduate training programs. This study explores specialty residents' perceptions of the impact of the University of Calgary's (UC) distributed education rotations on their self-perceived likelihood of practice location, and if this effect is influenced by resident specialty or stage of program. METHODS: Residents participating in the UC Distributed Royal College Initiative (DistRCI) between July 2010 and June 2013 completed an online survey following their rotation. Descriptive statistics and student's t-test were employed to analyze quantitative survey data, and a constant comparative approach was used to analyze free text qualitative responses. RESULTS: Residents indicated they were satisfied with the program (92%), and that the distributed rotations significantly increased their self-reported likelihood of practicing in smaller centers (p < 0.05). The findings suggest that the shift in attitude is independent of discipline, program year, and logistical experiences of living at the distributed sites, and is consistent across multiple cohorts over several academic years. CONCLUSION: The findings highlight the value of a distributed education program in contributing to future practice and career development, and its relevance in the social accountability of postgraduate programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".