Scholarly Opportunities for Medical Students and Residents in Canadian Medical Professional Organizations
Bibliographic record
Abstract
Objectives: Participation in medical specialty organizations can provide medical students and residents with additional research, advocacy, networking, and leadership opportunities. Although past research has looked at individual specialties in the United States, little is known about trainee involvement in Canadian organizations. Therefore, the aim of this study is to review the opportunities available for medical students and residents within Canadian medical specialty organizations. Methods: The websites of 71 Canadian medical specialty organizations were reviewed to assess levels of trainee participation. Results: Of the 71 organizations reviewed, 42 (59%) allow medical students and 67 (94%) allow residents to become members. Most organizations allow trainees to attend their annual conference (83% for students and 93% for residents), and the mean cost of attending the most recent virtual conference was $114 (range: $0-$475) for students and $142 (range: $0-$475) for residents. Twenty-two organizations (31%) have travel awards for students and 37 (52%) have awards for residents. Research grants are available in 41 (58%) of organizations for students and 56 (79%) for residents. Formal mentorship programs exist in 16 (23%) organizations for students and 25 (35%) for residents. Conclusion: To our knowledge, this study highlights for the first time the scholarly opportunities available to trainees within Canadian medical specialty organizations.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".