Searching for Our Alma Maters: Women Professors in Canadian Fiction Written by Women
Bibliographic record
Abstract
Campus fiction is typically character-driven and, in the hands of male writers, satirical and comic, exploring the lives and foibles of individual professors, institutional dynamics, and sexual politics. In the hands of women authors in Canada, however, campus fiction since the 1940s has been a more serious matter. An ill fit in the faculty body whoever she is, from prim spinster to pregnant feminist, the fiction’s academic women generally feel like “outsiders within” (Collins 2000). The 11 texts studied here serve as what Jean-François Lyotard calls “legitimating forms of discourse” (quoted in Tambling 1991, 98) on such issues as the dearth of role models for women professors, difficulties in finding a balance between work and life, professional self-doubt, marginalization, and sexual harassment. Articulating women’s perspectives and patterns of experience, these narratives, albeit fictional, are one way for academic women “to know ourselves” and possibly to plot 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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.059 | 0.023 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".