Global health initiatives and electives: a survey of interest among Canadian otolaryngology residents.
Bibliographic record
Abstract
OBJECTIVE: To determine the level of interest among Canadian otolaryngology residents in global health initiatives (GHIs) and international health electives (IHEs) and the barriers to participation in such initiatives. METHODS: A Web-based survey was developed and sent to all Canadian otolaryngology residents. Questions were posed on demographics, the level of interest in GHIs and IHEs, past experiences in this field, real and perceived barriers in pursuing GHIs and IHEs, previous global health experience, and, finally, the current infrastructure that exists in Canadian postsecondary institutions and otolaryngology programs to encourage participation. RESULTS: The level of interest among Canadian otolaryngology residents in GHIs and IHEs is at least 32%. The greatest barriers to pursuing this interest are cost, lack of infrastructure, lack of mentors, and lack of elective time. To contribute to an important cause was the top reason (79%) cited by respondents for their interest in global health. This was followed by personal growth and to learn about medicine in low- and middle-income countries, respectively. CONCLUSION: At least 32% of Canadian otolaryngology residents showed interest in participating in a GHI or IHE. We must devise means of overcoming barriers to participation in GHIs and IHEs and facilitate the clear and substantial resident interest in GHIs and IHEs. By supporting these endeavours, we will expose a cross section of physicians to global issues and give them an important and meaningful context in our increasingly interconnected world.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".