Increasing Support and Job Satisfaction for Program Administrators at the Postgraduate Medical Education Program at the University of Ottawa: The Program Administrator’s Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract . Background : Realizing Program Administrators (PAs) are crucial to the success of the postgraduate medical education (PGME) program, the PGME office at the University of Ottawa conducted a needs analysis to (a) identify training opportunities PAs felt would support them in being effective at meeting role expectations including supporting Program Directors (PDs) and (b) gather information from PAs to guide the PGME office in taking positive action toward increasing satisfaction with services and resources. Methods: A mixed methods approach involved collecting and analyzing data from online surveys and follow-up qualitative interviews. Data analysis was conducted using the constructs of the W(e)Learn framework (content, media (delivery), service, structure and outcomes). Results : PAs identified the following professional development topics they said would benefit them: Human Resources; Communication and Conflict Management Courses; Career Development; Evaluation; Policy; Multigenerational Workforces; and Best Technological Practices of Relevance to PAs . The PAs also identified several recommendations for how the PGME office could facilitate them effectively carrying out their roles and responsibilities. Conclusions: An effective form of support is offering convenient, relevant professional development to help employees meet role expectations. A well-designed professional development program should begin with a needs analysis to determine stakeholder needs with regard to relevant content, preferred delivery methods, service issues and course structure, in order to ensure desired learner outcomes.
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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 | 0.007 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it