Scottish Poets and English Stanzas: <i>Schir Thomas Norny</i> and Dunbar’s Use of Tail-Rhyme
Bibliographic record
Abstract
It is a tradition almost amounting to a rule for literary critics to praise the late medieval Scottish poet William Dunbar for his great variety and mastery of poetic technique. In terms of his exploration of stanzaic patterns, however, Dunbar is relatively conservative. In his shorter poems, he has a discernible preference for rhymed stanzas of four or five lines, usually made up of the four- or five-stress lines most prevalent in fifteenth-century English and Scottish poetry. He does not invent new metrical schemes nor does he use an especially large range of them, considering the number of poems he wrote. He does, however, show an unusual flair for marrying form and sense. W. H. Auden comments admiringly, “He knows exactly the kind of verse which will suit any given subject, exactly what can be got out of a metre or a stanza form.”.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".