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Record W6983487577

Moralizing Strategies in Early Greek Poetry

2018· other· en· W6983487577 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Research Online (The Open University) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryDidacticismAncient GreekFunction (biology)Expression (computer science)Style (visual arts)
DOInot available

Abstract

fetched live from OpenAlex

The articles collected in this volume were originally presented at a conference held at Memorial University, St John's, Newfoundland, in July 2015. \n \nMoralizing, in the sense both of didactic advice and of reflection on received wisdom, is a prevalent feature of ancient Greek literature. Didactic poetry was a long-established genre, first known to us from Hesiod, though with much older roots, but elements of didacticism are important to small-scale non-hexameter poetry, whose performance function is often explicitly to guide or advise its audience. Yet moralizing strategies are found in poetry whose aim is not simply to tell its audience how to live their lives, and a core aim of the conference on which this volume is based was to explore ways in which early Greek poetry uses implicit moralizing within a broader poetic framework. In other words, we are interested in exploring how moralizing is embedded in poetry whose overt goal appears to be something different (including, for example, entertainment, storytelling, or the expression of blame). The term “moralizing” may also imply a straightforward lesson for the audience, yet early Greek poetry often complicates any such “message” even as it gives it, and a further aim of the collection is to think about the status of the moral advice embedded in the performance. To what extent is direct advice questioned or undermined? How far can the audience trust the narrator and his or her perspective? \n \nThe articles in this collection address this question from different perspectives, and using different texts, but coalesce around a group of core themes and questions. One area of particular interest is the difference between explicit and implicit moralizing, and how the advice given by the two can be reconciled. Another overarching theme is the relationship between moralizing in lyric and how it is used in Homer and Hesiod. Lyric poetry (including elegy and iambus) frequently positions itself as in dialogue with the epic tradition, and borrows from and recasts epic motifs for its own purposes. Yet the performance context and imagined audience of lyric may differ from those of epic, and the strategies adopted by the poets vary accordingly. Many of the articles discuss beast fable and animal imagery, contesting the commonly-held idea (first proposed by Karl Meuli) that a fable does not carry a universal truth but rather a specific one to suit the context. Finally, questions of persona and poetic biography, and of the audience and performance context, play an important role in understanding how morality is disseminated and received.

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)0.006
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 score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.016
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.186
GPT teacher head0.422
Teacher spread0.236 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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