Bibliographic record
Abstract
William Herebert’s Middle English poems, which appear in his Commonplace Book (c. 1314), have been undervalued by scholars. Yet, far from being a lonely purveyor of an ungainly series of translations, Herebert instead was a skillful adapter of Latin hymns into dance songs. Echoing his contemporaries and following the example of St Francis, Herebert revised the forms of two Latin poems, ‘Gloria, laus et honor’ and ‘Popule meus, quid feci tibi’, into two English lyrics: ‘Wele, heriȝyng and worshype’ and ‘My volk, what habbe y do þe?’ In doing so, he dealt imaginatively with poetic form, liturgical content, concepts of time and matching words to music – and he ended up producing early examples of English carols. Herebert’s achievements in dance song demonstrate that the seemingly outrageous idea of the dancing friar is not as alien to religious devotions as one might expect. We conclude with speculations concerning the performance of Herebert’s songs.
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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 | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".