International concurrent course delivery: Bringing pragmatic research to the classroom
Bibliographic record
Abstract
Tele-health, or health care at a distance, is increasingly becoming a common form of health service delivery yet few academics are researching this field, and fewer are teaching about it. This presentation discusses the development and delivery of a highly innovative online course delivered internationally and concurrently. Through a review of early applications of the technology in the UK and Canada, the course highlights societal, economic and technological drivers and the benefits, opportunities, challenges and barriers to this type of service delivery. It allows students from Western University, Canada to engage with academics and students from the University of Sheffield, UK as the content is provided by academic leaders in the field from both Universities allowing students to gain an international, comparative perspective. Students on the course are exposed not only to the new technology, but to the best academics undertaking cutting-edge research to develop and mainstream them.
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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 | 0.137 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.023 | 0.027 |
| Open science | 0.005 | 0.029 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.015 | 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".