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Record W2810282927 · doi:10.4000/aitia.1979

Κραδίᾳ γνωστὸς ἔνεστι τύπος (Meleager, Anth. Pal. 5.212.4): Self-Reflexive Engagement with Lyric Topoi in Erotic Epigram

2018· article· en· W2810282927 on OpenAlexaff
Regina Höschele

Bibliographic record

VenueAitia Regards sur la culture hellénistique au XXIe siècle · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAllusionTopos theoryEvocationLiteraturePoetryArtIntertextualityPhilosophy

Abstract

fetched live from OpenAlex

Sarah Mace, in a 1993 article, brilliantly traced the usage of δηὖτε in Archaic lyric, where the widespread topos of “Love . . . yet again” not only evoks the speaker’s personal experience of repeated erotic desire, but also the recurrence of love’s overwhelming onset throughout the genre. When Hellenistic epigrammatists write about their eros several centuries later, they manifestly engage with this and other lyric topoi, marking their experience of love as something well-known from the erotic tradition: it is not least the knowledge of their lyric models that enables them (and their readers) to correctly diagnose amatory symptoms and identify erotic symbols as such. Although such metapoetic play is something we readily associate with Hellenistic poetry, the potential for self-conscious evocation of the poetic tradition and generic conventions is already inherent in Archaic lyric itself. The present article looks at these earlier instances of self-reflexivity in comparison with the modes of allusion we encounter in erotic epigrams. By delineating similarities and differences in the generic and/or intertextual self-awareness of Archaic and Hellenistic poets, it hopes to shed new light on the inner workings of allusion in different literary contexts.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.012
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.312
Teacher spread0.294 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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