The Sandwich Fellowship: A Subspecialty Training Model for the Developing World
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it