Profiles in Epidemiology: Dr. Larry Svenson
Bibliographic record
Abstract
Dr. Larry Svenson is a Canadian epidemiologist who has effectively merged academic and government roles. Born October 26, 1964, in Summerside, Prince Edward Island, Canada, Svenson graduated with a bachelor of science degree from the University of Alberta (Edmonton, Alberta, Canada) in 1988 after majoring in psychology and minoring in statistics. Svenson began his career as a research assistant in 1991 with the Alberta Ministry of Health. Realizing the opportunities for applied research to directly inform policy, he advanced in government while participating in collaborative research, coauthoring more than 140 publications before receiving his PhD from Manchester Metropolitan University, Manchester, England, in 2015. Svenson’s greatest contributions use administrative health data research to address health policy needs. In 1999, Svenson led the pilot and development of the National Diabetes Surveillance System, which established common administrative case definitions across Canadian provinces, thereby addressing heterogeneity in data collection and quality (1,...
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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 | 0.025 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".