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Record W3213415787 · doi:10.30853/phil210543

Image of a Fasting Girl in E. Donoghue’s Creative Work (by the Example of the Novel “The Wonder”)

2021· article· en· W3213415787 on OpenAlexaboutno aff
Milyausha Nazimovna Sayfullina, Farida Hanifovna Sakhapova, Aigul Ramilevna Petunina

Bibliographic record

VenuePhilology Theory & Practice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDiscourse Analysis and Cultural Communication
Canadian institutionsnot available
Fundersnot available
KeywordsIrishWonderGirlGeniusLiteratureOpposition (politics)Interpretation (philosophy)HistoryAestheticsArtSociologyArt historyPsychologyPhilosophyEpistemologyLawPolitical scienceLinguistics

Abstract

fetched live from OpenAlex

The paper analyses the novel “The Wonder” (2016) by the modern Canadian and Irish writer Emma Donoghue in terms of the synthesis of Irish and English allusions in it. The purpose of the research is to determine specificity of the interpretation of a fasting girl’s image, as well as the ways of actualising the motif of opposition between the Irish rural way of life and the English urban one. Scientific novelty of the research lies in the fact that the topic of the Great Famine (1845-1849) remains one of the main ones in Irish literature and requires a more detailed study in the context of the creative work of not only national geniuses but also modern writers, including E. Donoghue. As a result of the research, specific techniques used by the author to play on national stereotypes have been identified.

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)0.002
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.025
Scholarly communication0.0060.002
Open science0.0010.003
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 head0.058
GPT teacher head0.359
Teacher spread0.301 · 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
Published2021
Admission routes1
Has abstractyes

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