E-health and the Universitas 21 organization: 1. Global e-health through synergy
Bibliographic record
Abstract
The Universitas 21 (U21) organization funded a one-year project to examine global e-health. An e-health steering committee surveyed the opinions of e-health researchers at U21 member schools and conducted a literature review. Information about key themes was analysed and the findings were summarized. The steering committee recommended an eight-step strategy to establish a sustainable endeavour in global e-health. This included implementing a dissemination strategy within the U21 organization to engage a progressively larger community of faculty members and others, and translating e-health knowledge into global practice in those areas in which the U21 has special expertise. While the recommendations in the discussion paper are specific to the U21 organization, the e-health steering committee believes they can be generalized and applied to any globally minded educational or research institutions seeking to contribute to e-health.
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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 | 0.020 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".