Bibliographic record
Abstract
Nellie L. McClung (1873-1951) was an internationally celebrated feminist and social activist whose success as a platform speaker was legendary. Her earliest notoriety was achieved as a writer, and during her lengthy career she authored four novels, two novellas, three collections of short stories, a two-volume autobiography and various collections of speeches, articles and wartime writing, to a total of sixteen volumes. All this served as a “pulpit” from which McClung could preach her gospel of feminist activism and social transformation. She was convinced that God’s intention for Creation was a “Fair Deal” for everyone; and that Canada, particularly the prairie West, was a perfect place to begin to bring that about. Woman suffrage, temperance and the ordination of women were keystones in the battle — engaged, in contrast to contemporary stereotypes, with a wit and compelling humour that won over enemies as it delighted her allies. Literature as Pulpit explores Nellie McClung’s vision of a “better world,” and the impediments to it, as expressed through her novels and her feminist “tract,” In Times Like These . It addresses the profoundly anti-feminist context within which McClung was forced to make her arguments, and notes her indebtedness to other feminist writers and thinkers of her day. Throughout, McClung’s religion of “active care” emerges as a consistent and harmonizing theme which integrates her feminism and social activism into a single empowering vision for social change.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.029 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.176 | 0.110 |
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".