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Record W2792675022 · doi:10.3138/mous.15.1.4

Picturing a Truth: Beast Fable, Early <i>Iambos,</i> and Semonides on the Creation of Women

2018· article· en· W2792675022 on OpenAlexaffvenue
Christopher G. Brown

Bibliographic record

VenueMouseion Journal of the Classical Association of Canada · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsFableInvectiveComedyLiteraturePoetryNarrativeArtPhilosophyHistoryPolitics

Abstract

fetched live from OpenAlex

Semonides’ poem on women (fr. 7W) is the longest surviving specimen of early ἴαµβος. Despite its length, however, the poem remains elusive, and its generic affiliations with the tradition associated with Archilochus and Hipponax are unclear. Invective has often been seen to stand near the heart of ἴαµβος, and in antiquity Semonides was regularly aligned with Archilochus and Hipponax as an ἰαµβοποιός—perhaps even as the πρῶτος εὑρετής of the genre, according to some (Suda σ 431 Adler = test. 7a Pellizer–Tedeschi)—but there is little in the surviving fragments that supports this view, and it is perhaps a telling point that the name of Semonides’ personal enemy, preserved by Lucian (Pseudol. 2 = test. 12 Pellizer–Tedeschi), cannot be made to fit an iambic line without emendation. While fr. 7 seems to lack specific personal targets, it nonetheless employs strategies of abuse and mockery familiar from ἴαµβος and comedy. Of particular interest are the poem’s affinities with beast fable, which were also prominent in the epodes of Archilochus. Semonides does not use any particular narrative, but the creation of different women from a variety of animals recalls fables such as 50 and 240 Perry. It is the purpose of this article to explore the use of such fables in early ἴαµβος, with particular emphasis on Semonides’ poem. It is shown to reflect the influence of a particular kind of creation story that is also found in Hesiodic poetry and Old Comedy.

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)0.002
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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
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
Published2018
Admission routes2
Has abstractyes

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