A review of selection criteria for ophthalmology training in the Western world
Bibliographic record
Abstract
BACKGROUND: To (a) analyse, compare and learn from the global variations in ophthalmology training applicant selection criteria, specifically CV assessment, and (b) provide a discussion of evidence supporting such selection criteria. METHODS: An observational analysis on the selection criteria used to assess candidates applying to ophthalmology training programs within the US, Canada, European Union / European Economic Union (EU/EEA), United Kingdom (UK) and Australia and New Zealand (ANZ). Presence of a publicly available selection criteria policy for the 2025 intake was searched for on national and local college, society, federation and training program websites. The selection criteria employed for assessing applicant CV, and its associated scoring (if existent), were recorded for the included programs. Descriptive statistics was applied to these data. RESULTS: 174 accredited ophthalmology training programs were identified, and 51/174 publish a publicly available selection criteria policy. Overall, the most important criteria from ophthalmic training bodies in the Western world include research experience, academic achievements, particularly in the form of awards and prizes, references supporting evidence of favourable personal and professional characteristics, and evidence of involvement in extracurricular activities that produce evidence of a well-founded interest in ophthalmology. CONCLUSIONS: Each region adopts varying selection processes and frameworks, which, rather than reflect a standardised international approach to selecting an "ideal" ophthalmology trainee, perhaps select for the specific needs of the country and or training program. The study is limited by its observational nature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".