Thomas Becket in the South English Legendaries: Genre, Materiality, and Why the Reader Matters
Bibliographic record
Abstract
The South English Legendaries (SEL) is a thirteenth-century collection of saints’ legends. More than just a work of hagiography, this collection demonstrates late medieval genre hybridisation and literary experimentation in the legend of St. Thomas Becket, the twelfth-century martyred arch¬bishop of Canterbury, which exhibits a variety of genre-bending tropes. This project explores how poets incorporate the genre expectations of hagiography, historiography, and romance to capture the attention of a broad audience. The presence of these genres in the legend of Becket corresponds to three traditional perceptions of Becket: as a religious figure, a historical figure, and a legendary figure. Drawing on the fields of “New Philology,” genre theory, and reading reception theory, es¬pecially Jauss’ “horizon of expectations,” I argue that the SEL is a work of “edutainment” and explore the dynamic relationship between readers and their concepts of genre. I identify three types of readers—authors, scribes, and manuscript users—across three different stages of the SEL— composition, compilation, and reception—and examine how genre informed interpretation. The SEL poet participated in both secular and religious literary traditions to captivate a broad audience, while the scribes who copied, compiled, and disseminated the Becket legend employed paratextual manuscript features to encourage specific interpretations. Three historical figures, Robert of Gloucester, Sir John Prise, and Sir Robert Cotton, provide evidence of reading engagement to show how interpretations of the Becket legend evolved. The SEL Becket legend was composed as a romance, disseminated as a saint’s life, and read as a work of history.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".