Bibliographic record
Abstract
Anthony Welch'sThe Renaissance Epic and the Oral Past argues that the fictions of oral performance that Renaissance epic poems inherited from their ancient sources reveal evolving notions of authorship, history, and political authority in the early modern world.Welch's analyses of the ways poets such as Tasso, Ronsard, Spenser, and Milton imagined themselves as pre-literate "singers of tales" revisit a key problem for modern readers of this genre: the deployment of formal and thematic devices from a temporally, culturally, and religiously alien past in order to reckon with political, aesthetic, and confessional challenges in the historical present.Welch's images of oral performance thus work like A. Bartlett Giamatti's gardens, Michael Murrin's military technology, and Tobias Gregory's pagan deities.What is new is that the emphasis on oral performance offers insight into the epic poems' engagement with Renaissance historiography; particularly, how positivist narratives of historical emergence are complicated, on the one hand, by encounters with oral communities in the Americas, Wales, and Ireland and, on the other, by a growing skepticism about the mythic origins of modern political orders.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".