Katherine Parr, Translation, and the Dissemination of Erasmus’s Views on War and Peace
Bibliographic record
Abstract
This article offers new evidence of Katherine Parr’s activities as a translator by demonstrating that she translated two prayers from Erasmus’s Precationes aliquot novæ in 1544. The first, “A Prayer for Men to Say Entering into Battle,” appeared in all the editions of Parr’s Psalms or Prayers; the second, “A Prayer for Forgiveness of Sins,” was included only in sextodecimo editions. These newly recovered translations have important implications for our understanding of Parr’s involvement in Henry VIII’s war effort and for the history of the dissemination of Erasmus’s ideas in England. This study argues that Parr’s translations provide new evidence that she collaborated with Thomas Cranmer and Henry VIII in producing wartime propaganda but also that Parr reframed, edited, and distorted Erasmus’s prayers to promote Henry’s wartime needs. This data has additional repercussions because Parr was also the sponsor of the translation of Erasmus’s Paraphrases on the New Testament, a text that exhorted Henry and other princes to avoid war and embrace peace. Parr, then, was at the heart of two translation projects that were fundamentally at odds with one another, and her translations can be described as important interventions into Erasmus’s legacy in England.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".