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Record W2725518077

ALICE MUNRO, MARGARET ATWOOD E MARGARET LAURENCE: DESLOCAMENTOS EMPODERANTES DA MULHER E RECONFIGURAÇÃO DA ESCRITA DE AUTORIA FEMININA CANADENSE NA DÉCADA DE 1970

2017· article· pt· W2725518077 on OpenAlexaboutno aff
Luiz Manoel da Silva Oliveira

Bibliographic record

Venuee-scrita · 2017
Typearticle
Languagept
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanitiesArt history
DOInot available

Abstract

fetched live from OpenAlex

Resumo: Este artigo pretende demonstrar como Lives of Girls and Women (1971), de Alice Munro, The Diviners (1974), de Margaret Laurence e Lady Oracle (1976), de Margaret Atwood reorientam a escrita de autoria feminina no Canada na decada de 1970, periodo revolucionario no mundo que tambem ecoou no Canada pos-colonial, rural, provinciano e fragmentado nos niveis linguistico, religioso, identitario e cultural. Uma vez que a Segunda Onda do Feminismo influenciou varias escritoras canadenses de 1960 a 1980, nestes tres romances as protagonistas escritoras poem em xeque pressupostos patriarcais cristalizados; abordam claramente as questoes sexuais, de genero e identidade feminina; e implodem as restricoes de “esfera publica/esfera privada”, realcando a relevância dos deslocamentos emocionais, nacionais e transnacionais das protagonistas para o seu empoderamento subjetivo, processo emoldurado pela retomada dos rastros de uma tradicao de escrita feminina obliterada, usurpada e silenciada pelo patriarcalismo, mas que ressurge com contornos de diferenca da ficcao masculina, antes modeladora da representacao identitaria feminina na literatura. Para esse fim, dentre outros/as teoricas/os, contamos com Virginia Woolf, Toril Moi, Coral Ann Howells, Elaine Showalter, Mary Eagleton, Sandra Almeida e Eva Hoffman.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.503
Threshold uncertainty score0.988

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0160.007
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.036
GPT teacher head0.287
Teacher spread0.251 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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