Medieval Romance, Medieval Contexts
Bibliographic record
Abstract
The popular genre of medieval romance explored in its physical, geographical, and literary contexts. The essays in this volume take a representative selection of English and Scottish romances from the medieval period and explore some of their medieval contexts, deepening our understanding not only of the romances concerned but also of the specific medieval contexts that produced or influenced them. The contexts explored here include traditional literary features such as genre and rhetorical technique and literary-cultural questions of authorship, transmission and readership; but they also extend to such broader intellectual and social contexts as medieval understandings of geography, the physiology of swooning, or the efficacy of baptism. A framing context for the volume is provided by Derek Pearsall's prefatory essay, in which he revisits his seminal 1965 article on the development of Middle English romance. Rhiannon Purdie is Senior Lecturer in English, University of St Andrews; Michael Cichon is Associate Professor of English at St Thomas More College in the University of Saskatchewan. Contributors: Derek Pearsall, Nancy Mason Bradbury, Michael Cichon, Nicholas Perkins, Marianne Ailes, John A. Geck, Phillipa Hardman, Siobhain Bly Calkin, Judith Weiss, Robert Rouse, Yin Liu, Emily Wingfield, Rosalind Field
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".