Bibliographic record
Abstract
Noting the resurgence of popular and academic interest in epics across disparate media, this essay proposes a theory of the epic genre that transcends particular media and cultures. It seeks to reconcile discussions of the epic in Aristotle, G.W.F. Hegel, Georg Lukács, Mikhail Bakhtin, Erich Auerbach, and Northrop Frye, arguing that traditional definitions of epic narrative are instead subsets of a greater generic structure. The epic is, following Gregory Nagy and Franco Moretti, among others, a literary “super-genre” that encompasses as many other kinds of narrative as possible. The essay explains how epic narrative, disembedded from earlier oral poetry, is then situated in new cultural contexts. Using the Roman epic as a paradigm, the essay also outlines a fourfold framework within which the interrelationship of the epic's symbolic content can be assessed. It concludes by suggesting some of the implications this theory has for new media epics in postmodernity.
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 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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.046 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".