The Work of Veronica Strong-Boag
Bibliographic record
Abstract
The pieces in this cluster originated roundtable, “Veronica Strong-Boag, Canadian Feminist Historian: An Assessment and Appreciation” at the 2010 Canadian Committee on Women’s History conference held in Vancouver. A multiple award-winning feminist scholar who has published numerous books, edited collections, and journal articles, Veronica Strong-Boag has had an enormous influence on Canadian history in general and Canadian women’s and gender history in particular. Throughout an academic career which has now spanned almost four decades, Strong-Boag has taught undergraduates and supervised graduate students in history, women’s and gender studies, and education-al studies. Her impressive body of research includes historical studies of feminism, female pacifists, women in suburbia, E. Pauline Johnson, child welfare, adoption, and fostering. As the pieces in this cluster well illustrate, Strong-Boag is admired and respected by her feminist colleagues as an esteemed academic, supportive mentor, and committed feminist.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".