Bibliographic record
Abstract
Performing the Penitential Psalms in the Middle AgesIn his early fifteenth-century paraphrase of the Seven Penitential Psalms, commenting on Psalm 142: 10 'Doce me facere voluntatem tuam, Quia Deus meus tu es' ('Teach me to do your will, because you are my God'), the Franciscan friar Thomas Brampton remarks 'Teche me to performe thy wylle'. 1 'To performe' functions here as a translation of the Vulgate's 'facere'; an alternative translation would be, of course, 'teach me to do thy will'.But 'to performe' is a perfectly valid rendition of 'facere'; indeed, evidence that this word was used to denote a range of actions is provided by the Middle English Dictionary, which, among its definitions of 'performen', offers the following: (a)To act; accomplish (a deed, task, service, etc.), carry out from beginning to end, achieve, perform (a duty, an office, a crime, penance, etc.); make (a pilgrimage); ~up, ~out; (b) to carry out (a promise, agreement, command, threat, law, etc.), fulfill, comply with; satisfy (desire, lust); put into effect or into practice (a plan, purpose); follow (advice); of a dream: come true; ~wille, carry out the request or desire (of sb.), act under the sway (of sb. or sth.) 2 Of these possible sub-definitions, 'to carry out, fulfil, comply with' is most obviously relevant to Brampton. 3 The simple act of doing is clearly what
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".