Calabrese, Michael, Hoyt N. Duggan and Thorlac Turville-Petre, eds. 2008. The Piers Plowman Electronic Archive Vol. 6: San Marino, Huntington Library Hm 128 (Hm, Hm2). and Adams, Robert, ed. 2011. The Piers Plowman Electronic Archive Vol. 7: London, British Library, MS Lansdowne 398 & Oxford, Bodleian Library, MS Rawlinson Poetry 38 (R). Cambridge: Published for The Medieval Academy of America and the Society for Early English and Norse Electronic Texts by Boydell & Brewer. CD-ROM.
Bibliographic record
Abstract
Volumes six and seven of The Piers Plowman Electronic Archive (PPEA) mark a significant achievement for the work of the editors and contributors to the project. The omnibus project aims to provide not only colour digital images of the entire corpus of William Langland’s texts of Piers Plowman, from the medieval period through the sixteenth-century, but also electronic transcriptions of each manuscript (as explained by Duggan 2005). Volume six includes images and transcriptions from San Marino, Huntington Library Hm 128 (Hm, Hm2); volume seven includes images and transcriptions from London, British Library MS Lansdowne 398 and Oxford, Bodleian Library, MS Rawlinson Poetry 38 (R). Piers Plowman has traditionally received much scholarly attention, not only due to its status as a canonical poem surviving from the Middle English period, but also because Langland wrote three distinct versions of the poem (A, B, and C), and thus the poem offers much for the study of Middle English textual history, editorial theory, and reception theory.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.025 |
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".