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Record W2734640395 · doi:10.5539/ijel.v7n4p138

Rhetorical Structure of Superstitious Images in Coleridge’s The Rime of the Ancient Mariner

2017· article· en· W2734640395 on OpenAlexvenueno aff
Rufaidah Kamal Abdulmajeed

Bibliographic record

VenueInternational Journal of English Linguistics · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLiterary Theory and Cultural Hermeneutics
Canadian institutionsnot available
Fundersnot available
KeywordsHard rimeRhetorical questionNarrativeLiteratureLinguisticsDictionSalientSubject (documents)Rhetorical criticismPoetryPhilosophyAtmosphere (unit)HistoryPsychologyArtComputer sciencePhysics

Abstract

fetched live from OpenAlex

The Rime of the Ancient Mariner by Samuel Taylor Coleridge was written in a way to inspire fear and create a somber, dark and terrifying atmosphere to attract the readers’ attention and to steer the attention of the readers to the themes of supernatural events and deep superstitions, thus highlighting these salient themes.The main aim of this study is to highlight the superstitious images in The Rime of the Ancient Mariner and analyse them according to Hoey’s (1983) Problem-Solution Pattern of rhetorical structure of discourse analysis by showing how certain lexical items can signal the narrative structure of the whole texts. The discourse analysis of the stanzas that carry superstitious images shows that this theory is applicable not only to sentences but to poems as well. Stanzas as grammatical units with complete thoughts can be analysed as well since they have the same narrative structure. The results show that all the stanzas, the subject of the analysis, have the rhetorical narrative structure components. They are namely; situation, problem, response, evaluation whether positive or negative.

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)0.008
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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.010
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
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 head0.019
GPT teacher head0.259
Teacher spread0.240 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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