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Record W2337391472 · doi:10.14288/1.0087113

Conflict and character in Aeschylus’ Agamemnon

2009· article· en· W2337391472 on OpenAlexaff
Peter Gainsford

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCharacter (mathematics)PhilosophyArtLiteratureMathematics

Abstract

fetched live from OpenAlex

Beginning with the position that Aeschylus expresses in Agamemnon a conflict between the character of Agamemnon and his wife Clytaemestra, it is discussed what form that conflict takes, how it is depicted, and how it is understood by its intended audience. Next the function of the idea of character, and of individual characters, in that conflict and in the presentation of that conflict is examined. Finally the definitions formulated in these sections are used to examine the interdependence of the two ideas of conflict and character in the cases of the two main characters in that conflict, Agamemnon and Clytaemestra. It is found that the conflict is schematised as a cyclical sequence of acts of vengeance, rather than an intellectually articulated opposition of viewpoints as might be expected. It is, however, treated as such an opposition for dramatic convenience, and this is achieved by a two-party system of allegiances in which Agamemnon and Clytaemestra are involved. It is then found that characters maintain individualised identities as flesh-and-blood personae while participating in this conflict, by the coincidence ('overdetermination') of the two sets of motivations implied by this dichotomy. It is then found that the intellectual functions and emotive realism of Clytaemestra and Agamemnon respectively justify and condemn the character Clytaemestra within the context of the conflict, and respectively condemn and justify Agamemnon. It is concluded that the style of the play is intentionally ambiguous and that events in the play serve multiple functions so as to create an impressionistic structure through which the audience perceives the above aspects of the play.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.012
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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 designTheoretical or conceptual
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

Citations0
Published2009
Admission routes1
Has abstractyes

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