Arvind Thomas, <i>Piers Plowman</i> and the Reinvention of Church Law in the Late Middle Ages. Toronto: University of Toronto Press, 2019. xiv, 267 pp.
Bibliographic record
Abstract
Abstract: As the law and literature movement in law schools reminded us several decades ago and Hans-Georg Gadamer before that, law and literature share much cultural work in common: they tackle some of the same communal problems; they interpret and revise norms for conduct; they evaluate written sources; they weigh what constitutes authority; and they both use and invite similar hermeneutical methods. This is especially so with medieval canon law and Piers Plowman. That capacious dream vision is chock full of forensic elements – trials, lawyerly debates, confessions, penalties, acts of restitution, pardons – and it is studded with so many legal terms and maxims that John Alford compiled a book-length glossary of them. From the late fourteenth century, readers have been interested in the poem’s legal language and its profound rethinking of how society can reach justice, especially in economic transactions. Now Arvind Thomas examines how the B and C versions of Piers understand legal problems somewhat differently from canon law and use legal thought in new ways for different ends, types of what he terms “reinventing” canon law. To do this, he focuses on private sacramental penance, organizing his study around the penitential process: contrition, confession, restitution, and satisfaction.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".