Susan swan and the female grotesque Susan swan and the female grotesque
Bibliographic record
Abstract
Introduced to readers as “the tallest woman freelance writer in Canada”, Susan Swan belongs to a generation of writers whose experimental, innovative fiction has proved vital in the contemporary project of de/re/constructing narrative practice. Her 1983 novel The Biggest Modern Woman of the World constitutes an excellent example of what critic Linda Hutcheon has termed “historiographic metafiction”—”fiction that is intensely, self-reflexively art, but is also grounded in historical, social, and political realities” (Canadian 13). As a conscious engagement with social and historical contexts, such fiction aims at destabilizing and subverting accepted patterns of belief by reconceptualizing and narrating possible subjectivities. By means of intertextuality, especially parody, it engages in an ideological critique in terms of both sexual and national politics. Introduced to readers as “the tallest woman freelance writer in Canada”, Susan Swan belongs to a generation of writers whose experimental, innovative fiction has proved vital in the contemporary project of de/re/constructing narrative practice. Her 1983 novel The Biggest Modern Woman of the World constitutes an excellent example of what critic Linda Hutcheon has termed “historiographic metafiction”—”fiction that is intensely, self-reflexively art, but is also grounded in historical, social, and political realities” (Canadian 13). As a conscious engagement with social and historical contexts, such fiction aims at destabilizing and subverting accepted patterns of belief by reconceptualizing and narrating possible subjectivities. By means of intertextuality, especially parody, it engages in an ideological critique in terms of both sexual and national politics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".