Grub-Street Compilers at Work: New Sources for John Dunton's Ladies Dictionary (1694)
Bibliographic record
Abstract
IN our introduction and index to the Ashgate Publishing facsimile edition of the Ladies Dictionary published by John Dunton in 1694, we identified the sources of more than 95 per cent of its approximately 1950 entries, and can now comment on six further entries.1 We proposed in our edition that the entry ‘Town Beau Characterised’ (620–3; here and below, page numbers are those supplied in our edition to replace the multiple overlapping sequences of pagination of the original) ‘may reproduce a similar ephemeral text’ to Dunton’s pamphlet The parable of the top-knots of 1691, most of which is reprinted in The Ladies Dictionary as the entry ‘top-knots’ (639–43). In fact, ‘Town Beau Characterised’ reproduces the second half of the four-page pamphlet The parable of the puppies, or, The top-knots vindicated. This is a reply to The parable of the top-knots, on the last page of which it was actually advertised. It is plausible that The parable of the puppies was by Dunton too; this would explain the advertisement, and would also explain why a copy was available to the compilers of The Ladies Dictionary.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.119 | 0.037 |
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".