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Record W7005811363

The search theme in Alice Munro and Pedro Almodóvar: female characters

2019· article· en· W7005811363 on OpenAlexaboutno aff

Bibliographic record

VenueAmericanae (AECID Library) · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)NarrativePoetryGeorge (robot)Character (mathematics)Meaning (existential)Existentialism
DOInot available

Abstract

fetched live from OpenAlex

This article aims to reflect on the poetic images of the feminine, from the “theme of the search”, in the work of the Canadian writer Alice Ann Munro, more specifically in three short stories in the book Fugitive (2014) and the filmic transposition of these tales, by Pedro Almodóvar Caballero in the movie Juliet (2016). From the book, the selected stories were: "Occasion", "In a moment" and "Silence". These tales function as intertexts in Almodóvar's filmography. For the development of the article, we sought theoretical, critical and methodological support in comparative studies in literature and other arts, intermediate studies and studies on the theme of travel as existential displacements of female characters, which in their erasures configure the “theme of search ”, contemplating other potent derivations for literary creation as well as for filmic creation, for example, images of silence, archetypal images of the feminine, childhood memories, generating a movement of departures and arrivals rich in displacements of the feminine self. The study methodology used here allows us to reflect on the processes of intermediary and transcreation of the literary narrative to the filmic narrative, analyzing the basic operations of the filmic construction, which will result in the expansion and transformation of the literary sign. It has as theoretical bases Balogh (2005), Walter Benjamin (2010), Luis Claudio Costa (2010), Isla Duncan (2011), Michelle Gadpaille (1988), Brad Hooper (2008), George Woodcok (1986), Claus Clüver (2006), Santiago Kovadloff (2003), Elisabeth Badinter (1980), Mikhail Bakhtin (1996), among others.

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)0.003
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 score0.243
Threshold uncertainty score0.483

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.011
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.004
GPT teacher head0.228
Teacher spread0.224 · 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
Published2019
Admission routes1
Has abstractyes

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