Changing the face of medicine in Canada with Dr. John Murray Last, Public Health Scholar and Emeritus Professor at the University of Ottawa
Bibliographic record
Abstract
AbstractDr. John Murray Last, MB BS, is an Emeritus Professor at the University of Ottawa. Having been born in Australia in 1926, and having studied and worked in Australia, England, the United States, and Canada, Dr. Last has developed tremendous knowledge surrounding healthcare around the world. Dr. Last is a scientist, teacher, successful author, and public health scholar. His books are now used in schools of public health worldwide. In addition to having developed the “iceberg concept”, he has also served as a leader in the development of ethical standards for epidemiology and public health. In 2012, Dr. Last was admitted as an Officer of the Order of Canada to honour his contribution to the public health sciences. RésuméDr. John Murray Last, MBBS, est un professeur émérite à l’Université d’Ottawa. Étant né en Australie en 1926, et ayant étudié et travaillé en Australie, en Angleterre, aux États-Unis, et au Canada. Dr. Last a acquis de prodigieuses connaissances quant aux soins de santé à travers le monde. Dr. Last est un scientifique, enseignant, auteur à succès, et un spécialiste de la santé publique. Ses livres sont actuellement utilisés dans des écoles de santé publique à l’échelle mondiale. En plus d’avoir mis au point le concept « d’iceberg », il a aussi été un leader pour l’élaboration de normes d’éthiques en épidémiologie et santé publique. En 2012, Dr. Last a été nommé Officier de l’Ordre du Canada pour honorer sa contribution aux sciences de la santé publique.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.031 | 0.017 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.009 | 0.023 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".