Part-time faculty in academic surgical specialties: The view of Canadian chairs
Bibliographic record
Abstract
Background: The rising rate of physician burnout and decreased interest in pursuing careers in academic medicine has popularized the option of part-time faculty (PTF). However, the current status and role of PTF in academic surgical departments are not well-defined. Methodology: A survey was conducted to gather the perspectives of Canadian Surgical Department chairs in academic centers on the current status and role of PTF. Particularly, chairmen were asked to rate the advantages and disadvantages, perceived challenges, contributions, and overall satisfaction of PTF (on a 5-point Likert scale). Results: Forty-eight percent (40/83) of surveys were completed by surgical department chairmen. There was a large variety of responses for the advantages and disadvantages and challenges of PTF. Full-time faculty (FTF) was reported to contribute significantly more to research and teaching than PTF (85% and 12% for research, respectively, P < 0.01; 90% and 53% for teaching, respectively, P < 0.01). Despite a decreased contribution to research and teaching as compared to FTF, PTF was reported to enhance the quality and diversity of the faculty. Overall, satisfaction varied largely, with chairmen reporting greater satisfaction for FTF over PTF (P < 0.01). Discussion: The definition of PTF varied among chairmen, most being categorized into themes of time commitment, practice location, and salary. As a result, the variance in the precise role of what constitutes a PTF appears to contribute to the diverse perceptions of chairmen. The differences in contributions to the department among FTF and PTF appear nuanced. For instance, PTF was found to provide quality teaching; however, to a lesser extent than FTF. Conclusion: The perceived status of PTF within Canadian academic Surgical Departments is highly variable among chairmen. The following core competencies are addressed in this article: System-based practice, Professionalism, and Patient care.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".