Bibliographic record
Abstract
Romans laughed at a rich variety of comic entertainments, some surviving today only in fragments: scurrilous Fescennine verse, coarse, improvisational farce ( fabula Atellana ), mime ( fabula planipedia or riciniata ), drama featuring Italian characters in Italian settings ( fabula togata ). They also enjoyed the fabula palliata (a play dressed in a Greek cloak), in other words, a play set in Greece featuring Greek characters in Greek costumes. Deriving from Menander (fourth century bc) and other Greek writers, this kind of play also became known as New Comedy, in contradistinction to Old Comedy, the satirical, political, fantastic, obscene, and profound romps of the earlier Aristophanes (fifth century bc ). Both Greek and Roman New Comedy featured stock characters like the old man ( senex ), young girl ( virgo ), and clever slave ( servus callidus ); the action generally involved forbidden love affairs, misunderstandings, and confusions of identity. The works of two playwrights – Plautus and Terence – largely constitute the extant corpus of Roman comedy. Inventive and exuberant, Plautus ( c . 205–184 bc ) emphasizes musical elements and verbal jokes. His twentyone surviving plays include a mythological travesty ( Amphitruo ), deceptions ( Pseudolus, Epidicus ), confusions of identity ( Menaechmi, Casina ), a revels ( Stichus ), and a moral fable ( Captivi ). The six surviving plays of Terence ( c . 160 bc ) thoughtfully adapt conventions to explore human relations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.081 | 0.023 |
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".