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Record W3146670035 · doi:10.1017/9781108771658.002

Premises and Expectations of the Elegiac Grotesque

2020· book-chapter· en· W3146670035 on OpenAlexaff
Mariapia Pietropaolo

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElegyElegiacBeautyComedyTheme (computing)ArtAestheticsLiteratureInvectiveDialecticComicsPerspective (graphical)ArtificialityDisfigurementPhilosophyVisual artsPoetryEpistemology

Abstract

fetched live from OpenAlex

Roman elegy makes frequent use of themes of ugliness and disfigurement, juxtaposing them with images of ideal beauty and sentiment. In order to overcome the obstacles to his erotic relationship, the poet–lover repeatedly represents his rivals and opponents in such a way as to ridicule their appearance and to degrade their social standing. My purpose in this study is to explore the theme of corporeal, intellectual, and social degradation from a perspective attentive to the aesthetic significance of the grotesque imagery with which such degradation is accomplished. I undertake to show that the grotesque plays a significant role in the self-definition of the genre in which it is least expected. Grotesque and idealizing imagery constitute the polarities of a dialectic that lies at the core of elegy. Classical scholars have long been interested in the use of grotesque imagery in such genres as comedy, invective, and satire. There is a sophisticated discussion of the grotesque in these areas of classical literature, which are concerned in part with themes of transgression and excess. Grotesque imagery occurs frequently also in elegy, a genre that foregrounds love and beauty.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.982
Threshold uncertainty score0.550

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.231
Teacher spread0.198 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2020
Admission routes1
Has abstractyes

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