Bibliographic record
Abstract
This paper presents a new interpretation of Euripides' Electra centred on the issue of hereditary excellence.The question of how nobility is to be defined and recognised forms a unifying theme of this work and is of crucial importance for the development of the plot.It is argued here that nobility is key to understanding two much discussed passages: the great speech of Orestes and the recognition scene.Key words: Tragedy, Euripides, Greek Poetry, Electra, Orestes 'perverse anagnorisis' by means of the scar as an explicit 'invitation to the audience to "recognise" the scene's poetic pedigree'.7 In her recent study of metapoetry in Euripides, Torrance has similarly viewed the recognition scene in the Electra as an 'invitation to reflect on the conventions of dramatic production'.8 Wohl echoes this approach in pointing out that the play raises and then seemingly dashes the prospect of a demotic hero in the farmer.The purpose of this volte-face is, she assumes, to show the limitations of a genre dedicated to the glorification of aristocratic heroes.9 From this perspective, the problem is not textual but a failure to understand the play's metapoetics.Halporn and Cropp, however, have stressed that, though Euripides may well be evoking previous versions of the myth, all parts of the text should nevertheless be relevant to the development of the plot in some way.10 What is needed is a coherent scheme or structure that might excuse the play's eccentricities and explain elements seemingly unmotivated by the plot.11 Some have supposed that Euripides' aim was to develop (and potentially highlight deficiencies in) the psychological character of his dramatis personae, an approach which has been endorsed most recently in Van Emde Boas' examination of language and characterisation in the Electra.12 Cropp points out that Orestes' apparently 'snobbish and superficial' musings on the criteria for nobility are in fact both a necessary part of his disguise and, ironically, a set of standards 'applicable to his own conduct [that] will be 7 Goff (1991) 261; cf.Goff (2000) 93. 8 Torrance (2013) 15. 9 Wohl (2015a); (2015b) 62-85; cf.Michelini (1987) 229-30.10 Halporn (1983) 105-6; Cropp (2012) 176.11 See e.g.Morwood (1981) 368 for a 'pattern from allure to destruction'.12 Van Emde Boas (2017) 61-2; on the negative portrayal of Electra see: Kitto (1939) 334 'callous to the verge of insanity'; Gellie (1981) 2-3: 'very ordinary and silly'; on Orestes see Denniston (1939) xxvii 'an unattractive character'; Kitto (1939) 338 'no bold hero'; Tarkow (1981) 147; Raeburn (2000) 155-6; on the deficiencies of such approaches, see however Lloyd (1986) and Michelini (1987) 187-98.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".