Vergil Redux: Transitional elements from Vergil’s Eclogues and Georgics adapted by 21st century poets.
Bibliographic record
Abstract
This thesis examines the ways in which three 21st century poets adapt Vergilian themes and text. There has been scant study of 21st century Vergilian poets, and so I take this opportunity to discuss such poets as a supplement to studies of previous poets in previous centuries. I analyze the 21st century poets’ uses of Vergil’s transitional themes from the Eclogues and Georgics, specifically ideas of the Golden Age, uses of transitional characters, and decline of the pastoral. The first chapter discusses Vergil’s uses of both the agricultural and Hesiodic Golden Ages, which the modern poets adapt and make relevant in 21st century contexts. The second chapter highlights three characters from Vergil’s Eclogues and Georgics, Alexis, Orpheus, and Hermes, and analyzes how they are adapted from Vergil as heralds of either the Golden Age or decline. The third chapter focuses on the decline of the pastoral, and specifically how the modern poets use Vergil’s imagery of the evicted farmers of the Eclogues to illustrate the decline of the 21st century landscape in socio-political and agricultural terms, as well as the decline of pastoral literature. I conclude this thesis by discussing the future of Vergilian pastoral literature in the contexts of other transitional themes and authors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".