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Enregistrement W4206294659 · doi:10.1353/phx.2014.0014

Exemplary Traits: Reading Characterization in Roman Poetry by J. Mira Seo

2014· article· en· W4206294659 sur OpenAlexvenueno aff
James J. O’Hara

Notice bibliographique

RevuePhoenix · 2014
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueClassical Antiquity Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPoetryReading (process)MythologyVariety (cybernetics)ElegyLiteratureOrder (exchange)AsideHistoryArtAestheticsArt historyPhilosophyComputer scienceLinguisticsArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

366 PHOENIX theoretical than the rest, but it looks at a variety of authors and genres to show how culture is, at heart, formalized memory. The analyses he offers of lyric, pastoral, and elegy all focus somehow on the aestheticization of the past, a hazy styling which at once obscures real history and keeps it alive in a formalized way. Meliboeus and Tityrus reenact the fall of the republic and the promise of the new age, respectively; Horace remembers and forgets the shield he dropped at Philippi by reformulating it as myth; Propertius’ obsession with Etruscan dust and bones joins life and death, and, moreover, constitutes life in death. Though this essay is dense and difficult, it is also a productive new line of inquiry. One example: would Schwindt’s model of culture as formalized memory still be valid in more “objective” genres, that is, those not characterized by a first-person subject, speaking alone or in dialogue? This volume is richly rewarding. Given its coherence and quality, it deserves a full reading from cover to cover rather than a piecemeal approach. It is even, dare I say, well worth the steep purchase price. Taken together, the papers raise enough questions that another conference is in order. There is much work for our field to do in the meantime. University of Kansas Tara S. Welch Exemplary Traits: Reading Characterization in Roman Poetry. By J. Mira Seo. New York: Oxford University Press. 2013. Pp. xi, 220. This revised Princeton dissertation opportunely and successfully takes advantage of recent advances in scholarship in several areas: intertextuality, or the ways in which each new text depends upon the reader’s knowledge that it is built from pieces of earlier texts (e.g., the work of Stephen Hinds et al.); exemplarity, or the “peculiarly Roman emphasis on model and emulation in ethics and poetics” (1, with special attention to the work of Matthew Roller); the study of how the definition of character in both Greek and Roman literature is different from that of modern literature and drama (e.g., the work of Christopher Gill); and a welcome focus on readers and reading in almost all modern work on Latin poetry.1 After an Introduction, five chapters treat Aeneas and Paris in Vergil’s Aeneid, Cato in Lucan’s Bellum Civile, Seneca’s Oedipus, and, in separate chapters, both the young warrior Parthenopaeus and the prophet Amphiaraus in Statius’ Thebaid. After a brief conclusion, an appendix discusses Hippolytus in Seneca’s Phaedra. No chapter is devoted to Ovid, but Ovid bulks large in the Introduction and in several chapters, both as a model for poets and as a touchstone for Seo. The book will be useful both for its individual readings, and because it offers a method that could profitably be used on many authors, or even other parts of the works Seo treats. Seo begins by explaining every word of her title. “Exemplary” will now be obvious, but “Traits,” “a term associated with genetics,” suggests that “literary characters may also demonstrate [their literary] heredity and genealogical affiliation through allusion” (1). “Reading Character” is meant to suggest first that “the composition of character” should be seen “as a literary technique to be interpreted and analyzed (through ‘Reading’) 1 S. Hinds, Allusion and Intertext: Dynamics of Appropriation in Roman Poetry: Roman Literature and Its Contexts (Cambridge 1998); C. Gill, The Structured Self in Hellenistic and Roman Thought (Oxford 2006); M. Roller, “Exemplarity in Roman Culture: The Cases of Horatius Cocles and Cloelia,” CP 99 (2004) 1–56. BOOK REVIEWS/COMPTES RENDUS 367 in its own right” (1, italics original). And “Roman Poetry” is meant first to flag the book’s special concern with “how Roman-ness is defined by this tradition so influenced by Greek models” and also to ask how character in “Poetry” is like and unlike that of “historiography, rhetoric, or philosophy” (2); Seo draws widely and productively from both prose texts and scholarship on prose authors. Her Introduction argues for “preconceived roles for author and audience in Roman literary production” (7) that in part explain why Roman characters seem “flat” to modern readers. Poets were expected to “take into account the expectations established by...

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,005
Communication savante0,0030,002
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,280
Écart entre enseignants0,264 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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