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About epic subject: heroes, heroines and anachronism

2021· article· en· W4213415018 on OpenAlexaff
Christina Ramalho

Bibliographic record

VenueRevista Épicas · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsHyperion Technologies (Canada)
Fundersnot available
KeywordsAnachronismEPICLiteratureMythologyPoetrySubject (documents)HERORepresentation (politics)ArtHistoryPhilosophyLaw

Abstract

fetched live from OpenAlex

Considerations about a special subject, the epic, or, in other words, the hero and/or the heroine who are the protagonists of some long poems which talk about history and myth in a literary way, with or without traces of anachronism. We will consider the evolution of concepts of subject as a fundamental category for literary studies, the evolution of the epic genre itself, the epic representation of women and the anachronism as a possible presence in epic poems. Illustrating our reflection we will comment some epic poems which integrate the epic expression in English: The faerie queene, by Edmund Spenser; Paradise regained, by John Milton; The Rape of the Lock, by Alexander Pope; The Fall of Hyperion, by Keats; Christ, by Gavin Bantock; and South America. Mi hija, by Sharon Doubiago.

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: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.998

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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
Published2021
Admission routes1
Has abstractyes

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