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Record W4377224973 · doi:10.52340/lac.2023.08.15

Women's Narrative in Alice Munro's Short Story Runaway

2023· article· en· W4377224973 on OpenAlexaboutno aff
Tamar Gelashvili

Bibliographic record

Venueenadakultura · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsAdventureCharacter (mathematics)NarrativeFlanneryLiteratureAlice (programming language)HistoryArtArt historyPhilosophyTheology

Abstract

fetched live from OpenAlex

Alice Munro, the contemporary Canadian English-language writer who proved the importance of the short story as a genre by receiving the Nobel Prize in 2013, is undoubtedly an interesting author in terms of researching women's narrative. Although most of Munro's stories are set in the Harron Country, by using those regional features, customs, and traditions, Munro creates universal texts just like William Faulkner and Flannery O'Connor of his time. Like Faulkner and O'Connor, Munro's characters often confront deep-rooted and time-worn customs or traditions, but Munro's characters' reactions are generally less severe than those of his Southern counterparts. In addition, Munro's male characters are of one type, monotonous and boring, while female characters are more complex, peculiar and distinctive. The present paper analyses Alice Munro's short story collection Runaway (2004), paying particular attention to the title story. The collection consists of eight short stories. The main unifier of the stories about women of seemingly different ages and statuses is the desire to escape, which is caused by various reasons (unhappy marriage, family problems, running away from a provincial town in search of adventure). It is also interesting that the second, third and fourth stories of the collection tell about the same character, Juliet, and different episodes and stages of her life, which Pedro Almadovar even made into a movie in 2016. While Munro divides the story of "Juliet" into three independent stories, but united by the main character, the eighth story of the collection is in five parts and covers the life of the main character, Nancy. This decision of Munro is not accidental, and with this action, he once again emphasizes the innovations he brought to the genre of the story.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.237
Teacher spread0.217 · 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 teacher head, not a consensus.

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
Published2023
Admission routes1
Has abstractyes

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