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КОМИЧЕСКОЕ В ТВОРЧЕСТВЕ МАРГАРЕТ ЭТВУД

2024· article· ru· W4406559099 on OpenAlexaboutno aff
Роксана Романовна Найденова

Bibliographic record

VenueBulletin of Udmurt University Series History and Philology · 2024
Typearticle
Languageru
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

Данная статья посвящена описанию и анализу работы комического в творчестве известной современной канадской писательницы М. Этвуд. Комическое в произведениях автора подается завуалированно. Избегая открыто пользоваться в своих книгах приемами по созданию комического эффекта, писательница играет и шутит с читателем при помощи сложной нарративной структуры. Юмор М. Этвуд основан на способе подачи материала, все ее произведения - это тотальное пространство ее героев-рассказчиков, чья цель заключается в том, чтобы привлечь слушателей и убедить их в своей правоте. Для этого они используют многие манипулятивные нарративные приемы при рассказывании истории. Например, создание и смена масок, псевдо-интрига, постулирование тезиса и его последующая карнавализация, разоблачение и др. This article is devoted to the description and analysis of the work of the comic in the creative art of the famous contemporary Canadian writer M. Atwood. The comic in the works of the author is presented in a veiled way. Avoiding open use of comic effect techniques in her books, the writer plays and jokes with the reader using a complex narrative structure. M. Atwood's humor is based on the way the material is presented, all her works are controlled by her storytelling characters, whose goal is to attract listeners and convince them that they are right. To do this, they use many manipulative narrative techniques when telling a story. These are, for example, the creation and change of masks, pseudo-intrigue, postulation of the thesis and its subsequent carnivalesque, exposure, etc.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0240.000

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 head0.011
GPT teacher head0.169
Teacher spread0.158 · 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
GenreOther

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

Citations1
Published2024
Admission routes1
Has abstractyes

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