Bibliographic record
Abstract
The Welsh Marches, a name that today refers to the borderland regions between England and Wales, are often coupled with images of idealized rusticity, of ‘blue remembered hills’. Yet, in the Middle Ages, the Marches stretched from the borders into much of modern-day Mid and South Wales and were important spaces of conflict, colonization, and contact; of complex, shifting, strategic politics and identities; and, crucially, of vibrant literary activity. An exploration of the Marches’ multilingual literary cultures, this book is structured around three geotemporal case studies: Hereford, c. 1170–c. 1210; Ludlow, c. 1310–c. 1350; and Ynysforgan, c. 1380–c. 1410. Analysing texts and manuscripts composed, copied, compiled, translated, or otherwise circulated in these locales, this study crosses linguistic and disciplinary boundaries to formulate readings of works in French, Welsh, English, and Latin. These readings are developed through an extended engagement with the philosophy of Bruno Latour, particularly his work on Actor-Network Theory and modes of existence. From these perspectives, this book not only situates the March within wider literary networks but also reads its texts as networking narratives that deconstruct binaries of centre and periphery, of local and global, of human and nonhuman, and even of reality and fiction themselves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.023 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".