Poetry and Politics in the Fourth c. AD: Optatianus Porphyrius’ figured poems and Claudius Claudianus’ Laus Serenae
Bibliographic record
Abstract
In this article, I analyse two specimina of imperial panegyrical poetry, addressed at persons who hold lower ranks in the imperial hierarchy than the emperor: Constantine’s son Crispus in the first quarter of the 4th century AD in Optatianus Porfyrius’ hexametric poetry, and Honorius’ cousin (and sister by adoption, as well as mother-in-law) Serena in the last quarter of the same century, praised by Claudius Claudianus in his Laus Serenae. The analysis fits into scholarship of recent decades focusing on imperial representation, also of secondary figures in politics. It will be concluded that in each instance, even if a person in the shadow of supreme power is praised, the highest reigning emperor is still the (indirect) object of imperial praise, be it in prose or verse panegyric.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".