A World of Difference : How universities must evolve in a post-COVID world
Bibliographic record
Abstract
Dr. Johnson has led several initiatives to mobilize research and influence policy. Prior to her appointment as president, she was SFU’s vice-president, research and international. She was also the Scientific Director for the Institute of Gender and Health at the Canadian Institutes of Health Research; in this capacity she is credited for ensuring gender is considered in health research. Dr. Johnson’s work has been recognized with numerous awards including the UBC Killam Research Prize, and the School of Nursing Centenary Medal of Distinction. She is an elected Fellow of the Canadian Academy of Health Sciences and a Fellow of the Royal Society of Canada, and has co-authored more than 180 peer-reviewed articles. In 2010, she was recognized as one of BC’s 100 Women of Influence, and in 2012 received the Queen Elizabeth II Diamond Jubilee Medal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.026 |
| Scholarly communication | 0.046 | 0.049 |
| Open science | 0.003 | 0.035 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.039 | 0.011 |
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".