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Record W3217139339 · doi:10.21971/pi29377

Love and Death in Latin Elegy

2021· article· en· W3217139339 on OpenAlexaffvenue
Heva Olfman

Bibliographic record

VenueCrossing boundaries · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElegyPoetryElegiacLiteratureTone (literature)Style (visual arts)Order (exchange)ArtIdeal (ethics)Philosophy

Abstract

fetched live from OpenAlex

Love and death is a common and shared human experience that many poets of the ancient world explored in their various poetic works. The elegists of Rome famously wrote love poems in which each pined for a specific mistress or lover, and in some of these poems, love and death were simultaneously prominent themes. In this article I examine the relationship between the concepts of love and death in Propertius 4.7, Tibullus 1.3 and Ovid’s Amores 3.9. From this study it is evident that each poet, through means of their own style, depicted the ideal that love had the ability to overcome death. To support my analysis of these texts and the issues surrounding them, I refer to Papanghelis, Hinds and Maltby. While these authors consider many aspects of Proptertius’, Tibullus’ and Ovid’s works, the relationship and connection present between love and death has not been significantly considered. In order to establish each poet’s personal style I begin with a brief overview of elegiac poetry; then, an examination of each poem’s tone, word usage and thematic distinctions. I will begin the discussion with Propertius’ poems; Tibullus’ and Ovid’s poems will then be considered, first separately, and then as a pair. The concepts of love, death and those affected by the death in the poem will be analyzed. In addition, I will consider how love and death interact with each other in the poems. To further supplement the discussion, I will analyze how these three poets’ write in the same genre and about the same topics, but in different contexts and styles. This analysis leads to an understanding that each poet expressed their unique style in their poems, while maintaining a similar theme and genre, that love has the ability to overcome the unavoidable and inevitable force of death.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.010
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.345
Teacher spread0.297 · 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
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

Citations0
Published2021
Admission routes2
Has abstractyes

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