Evaluation and Comparison of the Comprehensiveness of Canadian and American Ophthalmology Residency Program Websites
Bibliographic record
Abstract
We descriptively and comparatively evaluated the comprehensiveness of Canadian and US-accredited ophthalmology residency program websites as of August 28, 2024. Using Canadian Resident Matching Service (n = 15) and US Fellowship and Residency Electronic Interactive Database (n = 125), we assessed website content across seven criteria: recruitment, faculty, residents, education/research, teaching, benefits, and community. Two independent reviewers used a 40-point system, with Kruskal-Wallis and post-hoc pairwise tests for analysis by country and funding model. US programs more frequently had highly comprehensive websites than Canadian programs (US: 74.4%, Canada: 40%). Canadian programs mostly achieved moderate comprehensiveness (Canada: 60%, US: 22.4%). Larger program size and US origin were significantly linked to higher comprehensiveness scores (p < .01). Our findings suggest that US-based, larger programs offer more extensive online resources. We recommend standardized guidelines to improve residency program website transparency and accessibility for medical learners.
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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 | 0.014 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".