Scholarly Success Among Internal Medicine Residents in Canada
Bibliographic record
Abstract
Scholar activity is an integral component of postgraduate medical education in Canada. We describe the opportunities in research training among Canadian internal medicine (IM) programs, including program requirements and supportive infrastructure, as well as barriers and enablers of research success. Methods: An email survey was sent to all program directors (PDs) ( n = 14) and core IM residents ( n = 1119) from English-speaking IM Residency Training Programs in Canada to describe research support and productivity. We evaluated factors associated with achieving an abstract presentation at a scientific meeting or publication of a manuscript in a peer-reviewed journal. Results: A total of 10 of 14 PDs (71%) and 308 of 1119 residents (28%) responded to the survey. Of 10 evaluable programs, 6 had a formal research curriculum and 8 had a mechanism of pairing residents with research mentors. A total of 236 (76%) residents completed a research project during core IM training; of those, 171 (55%) published ( n = 84) or presented ( n = 150) their research. A mechanism for linking residents with suitable research mentors, instruction on medical writing, and instruction on data analysis were associated with residents’ achieving publication in a peer-reviewed journal. Conclusion: Requirements for resident research are variable across Canadian IM programs. Instruction on medical writing and statistics, as well as a mechanism to pair residents with suitable research mentors, contribute to resident research success.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".