A Framework for Sustainable Implementation of E-Medicine in Transitioning Countries
Bibliographic record
Abstract
Organizations in developed countries such as the United States of America and Canada face difficulties and challenges in technology transfer from one organization to another; the complexity of problems easily compounds when such transfers are attempted from developed to developing countries due to differing socioeconomic and cultural environments. There is a gap in the formation of research and education programs to address technology transfer issues that go beyond just transferring the technologies to sustaining such transfers for longer periods. This study examined telemedicine transfer challenges in three Sub-Sahara African countries and developed a framework for sustainable implementation of e-medicine. Both quantitative and qualitative research methods were used. The study findings indicate that e-medicine sustainability in Sub-Saharan Africa is affected by institutional factors such as institutional environment and knowledge management practices; technical factors such as the technological environment and technology transfer project environment; social environmental factors such as social environment and donor involvement. These factors were used to model the proposed framework.
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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 | 0.000 |
| 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".