Feature Story: Lecture has special meaning for Dean of Education
Bibliographic record
Abstract
Dr. Jennifer Tupper has been invited to give the Dr. Ottilia Chereka Memorial Lecture in Education and Social Justice at the University of New Brunswick on February 19. “I knew Dr. Chareka before she was murdered by her husband and we shared similar commitments to social justice education,” says Dr. Tupper who is acting Dean of the Faculty of Education. “It means so much for me to be invited to speak at the lecture.” Dr. Ottila Chareka, originally from Zimbabwe, was a professor in the Faculty of Education at the University of St. Francis Xavier. She arrived in Canada in 1993 and earned three degrees at the University of New Brunswick. Her research focused on bringing marginalized groups such as Aboriginal people into more prominent positions in society. She was respected by academics, adored by the community and was a role model for African-Canadians and First Nations women.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.221 | 0.107 |
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".