Plautinopolis: Imagination and Representation in Plautus' Roman Comedy
Bibliographic record
Abstract
Scholarship on self-referentiality in Plautus’ Roman comedy has historically concentrated upon metatheater, highlighting the artificiality of performance conventions but largely taking the content of his plays as reflective of contemporary Greco-Roman reality, however stylized. By identifying a broader range of self-referential effects at work in his plays, including metageneric commentary upon the characters and plots of the New Comic tradition, I demonstrate that Plautus calls attention to the artificiality not only of their performance but also of their content. Plautine comedy is not set in the real world, I argue, but in a made-up, conventional location, “Plautinopolis.”Informed by scholarship on the worlds of science fiction and fantasy media, my first chapter offers a systematic model of Plautine generic conventions, conceptualizing them as the rules of an imaginary world in which all Plautus’ surviving plays are set. My second and third chapters propose that in emphasizing Plautinopolis’ artificiality, the plays’ self-referential effects encourage spectators to gain competence in the generic and theatrical conventions that define it; approaches from fan studies, theater semiotics, and narratology elucidate the processes through which viewers do so. Readings of Mercator in Chapter 2 and Poenulus in Chapter 3 illustrate how characters, too, may gain competence, and I argue that by habitually giving happier endings to more competent characters, Plautus shows spectators the stakes of understanding his play-world. With a reading of Curculio’s choragus speech, my final chapter argues that the imaginative worldbuilding that Plautine comedy encourages creates immersive effects through which spectators may participate as co-creators in playmaking. Recognizing the role that metagenre plays in reinforcing Plautinopolis’ artificiality reveals Plautus’ innovation in the representative dynamics of the New Comic tradition, which he casts as distinct from other theatrical genres in its aesthetics and relationship to its spectators. The imaginative demands that Plautine comedy makes of its viewers show Plautus’ persistent concern with their appreciation of drama as not merely a representative project, but a creative one, as well. The implications of this new model of Plautine representation extend from theater history to historicist work on Roman comedy to reception studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".