“The Challenge of an Ancestor of the Earl of Warwick”: The Guînes pas d'armes of 1413
Bibliographic record
Abstract
On January 6-8, 1413, in a field outside Guines, near Calais, an English knight fought in an elaborately staged tournament against three French knights on three successive days, revealing his identity only on the last day. This exploit is enthusiastically described in two sources: the Beauchamp Pageant, British Library MS Cotton Julius E.iv, art. 6, fols. 13v-16r; and the text presented here, from British Library MS Lansdowne 285, the “Grete Boke” of Sir John Paston. Although the narrative does not name its protagonist, referring to him throughout as “the seide lorde,” “my lorde,” or “my seide lorde,” he was clearly Richard Beauchamp, Earl of Warwick (1401-39), as the independent account of this event in the Beauchamp Pageant attests. According to Enguerrand de Monstrelet, the Earl of Warwick was campaigning in the Calais area at the end of 1412; he must therefore have spent Christmas in Calais before staging this event.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".