Bibliographic record
Abstract
This essay discusses two categories of eighteenth-century comic verse that were mainstream in their time but are now almost forgotten. They have little or nothing to do with the satiric traditions that dominate critical attention. Part 1 explores a mass of comic verse tales, direct descendants of the medieval fabliau. In the process, it explores a best-selling anthology of them, the Noble brothers' The Muse in Good Humour (1744–85), and the career of Matthew Prior, the greatest contemporary producer of this genre and by far the most prominent English poet between Dryden and Pope. While often offensive in content, eighteenth-century verse tales remain quick and colloquial, still leaping off the page after 250 years. Their easy tetrameter couplets and plain diction remind us that neoclassical strictures only stretched so far. Part 2 introduces a stranger and less-appealing set of texts: cruel poems about physical defects and disabilities. Few texts could be more alien to current norms about the eighteenth century as an Age of Sensibility. Yet these “deformity poems” were produced in vast quantities and in every conceivable form, from epigrams about squinters, to long and absurdly sentimental tales about hunchbacks in love. Both professionals and amateurs seem to have used them as technical exercises—as a way of amusing themselves and showing off their skill at mimetic versification. As such, deformity poems illustrate the everyday uses of verse in this culture: they were written by everyone, circulated in and out of print, and constantly adapted to new audiences and new occasions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".