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Record W2598507924 · doi:10.5817/cejcs2002-2-2

Somatization of writing and semiotization of the body : a study of selected texts by English-Canadian feminist writers

2002· article· en· W2598507924 on OpenAlexaboutno aff
Eugenia Sojka

Bibliographic record

VenueThe Central European journal of Canadian studies · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGender studiesLiteratureSociologyLinguisticsHistoryPsychologyArtPhilosophy

Abstract

fetched live from OpenAlex

This study focuses on the analysis of selected texts by English Canadian feminist writers who are engaged in the conscious process of subverting / carnivalizing the coded discourse of patriarchal culture, which reinforces the heterocentrism, classism, racism and sexism of society. Betsy Warland, Daphne Marlatt, Lola Lemire Tostevin, Gail Scott, Erin Mouré and others challenge the traditional way of writing by deconstructing the linear alphabetical notation and writing a discourse translating the body into a script. Aware of recent development is the feminist discourse, the writers experiment with the translation of various senses of the body into writing. The body translated into writing somatizes the process, while the body itself is being semiotized, read as a linguistic sign or structure. The texts are read as an enactment of female desire, of female economy of language, the economy of plenitude, translated into the never-ending process of the eroticization of language. The rhetoric exploring the visual, the aural, the tactile and the olfactory experience ofthe body is examined here. The writers' penchant for linguistic play is not purely aesthetic. It helps us reflect on languages and the way they shape our thinking and acting in the world.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.011
Science and technology studies0.0440.030
Scholarly communication0.0120.003
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.021
GPT teacher head0.214
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueThe Central European journal of Canadian studiesSame topicDiscourse Analysis in Language StudiesFrench-language works237,207