Robert Radcliffe’s Translation of Joannes Ravisius Textor’s <i>Dialogi</i> (1530) and the Henrician Reformation
Bibliographic record
Abstract
Joannes Ravisius Textor’s Dialogi aliquot festivissimi (1530) exerted considerable influence in England in the 1530s. The English Textor movement was spurred primarily by the dialogues’ effectiveness in advancing and popularizing specific religious changes promoted by the government as part of the unfolding Henrician Reformation. Around 1540, the master of Jesus College School in Cambridge, Robert Radcliffe, dedicated a collection of prose translations of Textor’s three dialogues—A Governor, or of the Church (Ecclesia), The Poor Man and Fortune (Pauper et fortuna), and Death and the Goer by the Way (Mors et viator)—to Henry VIII. Radcliffe’s translations, especially the politically charged A Governor, demonstrate that not only his strategically selected source texts but also his method of translation helped him position himself in influential court circles and shape his image as a humanist scholar, schoolmaster, and translator. Les Dialogi aliquot festivissimi (1530) de Joannes Ravisius Textor ont exercé une influence importante en Angleterre pendant les années 1530. Le succès du mouvement anglais de Textor est principalement dû à l’efficacité avec laquelle les dialogues mettent de l’avant et popularisent des transformations religieuses spécifiques que promouvait le gouvernement dans le contexte du déploiement de la Réforme d’Henri VIII. Autour de 1540, le maître du Jesus College de Cambridge, Robert Radcliffe, a dédié une collection de traduction en prose des trois dialogues de Textor — A Governor, or of the Church (Ecclesia), The Poor Man and Fortune (Pauper et fortuna), et Death and the Goer by the Way (Mors et viator) — à Henri VIII. Les traductions de Radcliffe, en particulier celle du A Governor chargé politiquement, montrent qu’il a cherché à se positionner dans des cercles de cour d’influence et se construire une image de chercheur, d’écolâtre et de traducteur humaniste, non seulement à l’aide de ses choix stratégiques de textes à traduire, mais aussi à travers ses méthodes de traductions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".