Development of a pediatric ophthalmology academic partnership between Canada and Ethiopia: a situational analysis
Bibliographic record
Abstract
BACKGROUND: Educational capacity building in pediatric ophthalmology is necessary to address the burden of childhood blindness in Ethiopia. Residency and fellowship training at Addis Ababa University (AAU) have been enhanced with support from the University of Toronto (UofT), following the established Toronto Addis Ababa Academic Collaboration (TAAAC). Our aim was to assess the feasibility of implementing a pediatric ophthalmology fellowship at AAU with support from UofT, modeled by successful postgraduate medical education within TAAAC. METHODS: A situational analysis, including a needs assessment, was conducted at Menelik II Hospital, Addis Ababa. Staff expertise, equipment and infrastructure were compared to International Council of Ophthalmology fellowship guidelines. Patient volumes were assessed through medical chart review. Local training needs were evaluated. A strategic working meeting facilitated program specification. RESULTS: The faculty consisted of 11 ophthalmologists, including 2 pediatric specialists. Fourteen thousand six hundred twenty-seven medical and three thousand six hundred forty-one surgical pediatric cases were seen in the previous year. A 2-year fellowship incorporating anterior segment, retinoblastoma, strabismus, and retinopathy of prematurity modules was developed. Research collaborations, didactic teaching, and surgical supervision were identified as priorities requiring support. Quality standard indicators included faculty feedback, case log review and formal examination. Telemedicine, development of a larger eye hospital and partnerships to support equipment maintenance were identified as strategies to manage implementation barriers. CONCLUSIONS: The situational analysis provided a way forward for the development of a pediatric ophthalmology fellowship, the first of its kind in Eastern Africa. Learning outcomes are feasible given high patient volumes, qualified staff supervision and sufficient equipment. Strategic partnerships may ensure resource sustainability.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".