New Formalism and the Forms of Middle English Literary Texts
Bibliographic record
Abstract
Abstract Recent work in Middle English literature addresses the emerging relationship between formal analysis and book history. This article, emerging from the 2009 Conference on Editorial Problems in Toronto, seeks to clarify the way in which formalist approaches intersect with trends in English literary manuscript studies. How, we ask, can the lively field of book history take new direction through contact with the ‘new formalisms’ articulated in literary studies? More precisely, how does the form of the medieval book produce literary meaning in a distinctive and historicizable manner? We explore critical approaches to the formal features of medieval manuscripts, addressing medieval and modern theories of the book’s form, the relationship between written and oral forms of texts, the dialect of scribes, authorial composition of manuscripts, scribal corrections, the layout and illustration, and the binding of the codex. We suggest that close readings of manuscript form can shed light on aspects of texts obscured by the printing technology and formatting changes of modern editions. Furthermore, we point to new avenues for contextualizing the book within late medieval literary culture.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".