Calling all Emerging Health Leaders: A unique professional development opportunity awaits you!
Bibliographic record
Abstract
The Health Leadership Academy (HLA) is a joint venture between McMaster University's DeGroote School of Business and Faculty of Health Sciences. As part of a landmark gift from Michael G. DeGroote, the HLA strives to have a transformative impact on global healthcare by nurturing a community of future leaders through interdisciplinary and forwardthinking approaches to education, public events and research. Operating out of the Ron Joyce Centre in Burlington Ontario, the HLA creates transformative impact by developing tomorrow's health leaders at all levels of the health system with new ways to think and do within a rapidly evolving health environment. The Emerging Health Leaders (EHL) program is one of the Academy's key educational programs. A two-week intensive, residential leadership program for students and young professionals, EHL bolsters the skills of individuals seeking to make a difference in the health landscape.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.064 | 0.048 |
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".