Bibliographic record
Abstract
What does it mean to tell a story from a woman’s point of view? How have Canadian anglophone and francophone writers translated feminist literary theory into practice? Avant-garde writers Daphne Marlatt and Nicole Brossard answer these, and many more questions, in their two groundbreaking works, now made more accessible through the careful, narratological readings and theoretical background in Narrative in the Feminine . Susan Knutson begins her study with an analysis of the contributions made by Marlatt and Brossard to international feminist theory. Part Two presents a narratological reading of How Hug a Stone , arguing that at the deepest level of narrative, Marlatt constructs a gender-inclusive human subject which defaults not to the generic masculine but to the feminine. Part Three proposes a parallel reading of Picture Theory , Brossard’s playful novel that draws us into (re-) readings of many other texts written by Brossard, Barnes, Wittig, Joyce, de Beauvoir, Homer...to name a few. Chapter 12 closes with a reflection on the expression <’e>criture au f<’e>minin — a Qu<’e>b<’e>cois contribution to an international theoretical debate. Readers who care about feminist writing and language theory, and students and teachers of Canadian literature and critical and queer studies, will find this book invaluable for its careful readings, its scholarly overview, and its extension of the feminist concept of the generic. Not least, the study is a guide to two important works of the leading experimental writers of Canada and Quebec, Daphne Marlatt and Nicole Brossard.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.033 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".