Infectious Diseases Training in Canada: One Size Does Not Fit All
Bibliographic record
Abstract
PURPOSE: To evaluate training in infectious diseases, determining which components of the training program best prepare residents for their career choices and where improvements are needed.METHOD: A cross-sectional survey was mailed to all 14 physicians who had graduated from both the Adult and Paediatric Infectious Diseases Training Program at the University of Calgary from 1985 to 1998. Responses about the adequacy of training were measured using a Likert-type scale and a qualitative questionnaire.RESULTS: Of 14 mailed questionnaires, nine responses were received (64%). Two-thirds of respondents were in an academic setting, and seven (78%) graduates obtained postfellowship training. The specialists in academic settings were all engaged in multiple nonclinical activities. The clinical and diagnostic microbiological components of training received the highest scores in terms of adequacy of training.CONCLUSION: Graduates of the University of Calgary training program indicated an overall satisfaction with their training. However, improvements are needed in career counselling, health administration, antibiotic utilization, infection prevention and specialized outpatient clinics. Potential strategies for addressing these issues include didactic lectures, enhanced exposure to clinical outpatient settings and provision of designated faculty mentors.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".