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Record W2477022036 · doi:10.1017/ccol9780521860543.013

Staging rhetoric in Athens

2009· book-chapter· en· W2477022036 on OpenAlexaff
David Rosenbloom

Bibliographic record

VenueCambridge University Press eBooks · 2009
Typebook-chapter
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDemocracyVictoryPoliticsComicsLiteratureDramaRhetoricComedyArtSociologyMedia studiesLawPolitical sciencePhilosophyLinguistics

Abstract

fetched live from OpenAlex

Why tragic and comic poets, with their divergent approaches to drama, converge in their ambivalence to democratic oratory, is a fascinating question, since on the face of it, dramatists and orators have much in common. Like orators, dramatists were citizens of Athens authorized by the democracy and occupied a prestigious place within the city’s speech regime. Dramatists, like orators, competed for victory before mass audiences, though five judges randomly selected from a pool of ten determined victory in dramatic contests, not a majority of spectators. Their audiences, though not identical, overlapped; Demosthenes calls jurors as witnesses to events that transpired in the theater (21.18, 226). As Simon Goldhill writes, “to be in an audience is not just a thread in the city’s social fabric, it is a fundamental political act.” Most scholars believe that performances of tragedies and comedies at festivals in honor of Dionysus, god of wine and life-giving liquids, were in some sense political. How political were they? This essay discusses the anatomy of fifth-century theater’s negative engagements with democratic oratory and orators and suggests that its symbolic violence towards democratic speech regimes aroused a potentially anti-democratic nostalgia for a fictionalized time of unitary socioeconomic, political, and moral orders, the time of the fathers expressed in the slogans “ancestral constitution” and “ancestral laws.”

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.985
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.250
Teacher spread0.211 · 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
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

Citations5
Published2009
Admission routes1
Has abstractyes

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