The Sandwich Fellowship: A Subspecialty Training Model for the Developing World
Bibliographic record
Abstract
Health care systems in many developing countries are rapidly evolving to respond to urbanization and shifting epidemiological profiles, creating an environment favorable for subspecialty development. The struggle for developing nations to train and retain highly skilled clinicians within academic institutions has highlighted the need for creative approaches to subspecialty education in these regions. The "Sandwich fellowship" is an educational model in which a fellow completes rotations at an academic institution in the developed world as well as in his or her home environment. An important component of the model is the expansion of institutional capacity at the fellow's home institution to create an enabling environment to practice newly acquired skills. The fellowship provides experience in diverse geographic and cultural contexts under the guidance of a preceptor from an institution in the developed world who teaches in both settings. Preceptors are given opportunities to continue professional growth and gain from exposure to pathology not commonly seen at home. Successful pilots of a Sandwich fellowship took place in ophthalmology and orthopedic surgery at the University of Ottawa in 2007-2008 and required funding from multiple sources with bilateral institutional support. Emphasis was also placed on teaching, leadership, management, and research so the fellows could return home and lead the development of their subspecialty areas. Early contact between administrations enables the model to serve as a gateway to a long-term partnership between developed world academic establishments and developing world institutions. Such a relationship yields a mutually beneficial exchange of knowledge and skills. Beneficiaries include the hospitals, their staff, and patients at both institutions.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".