J. Matlock's <i>Young ladies guide to the knowledge of the English tongue</i> (1715): contextualising the first grammar of English for ladies
Bibliographic record
Abstract
Abstract Recently rediscovered, The Young Ladies Guide to the Knowledge of the English Tongue (1715) is now the earliest known grammar of English for females. After considering its possible authorship by the writing master John Matlock, I use his residence of Lichfield to exemplify the various ways in which girls might acquire vernacular literacy. Drawing on the Eighteenth‐Century English Grammars database (ECEG), I compare the Guide with contemporary grammars and spelling books, linking its latinate lexis, ‘ungrammatical’ sentences and non‐traditional grammatical terms and categories to an audience of Ladies who are stereotypically not classically educated but nonetheless distinct from charity school girls. I also contextualise this text in such ongoing changes as the movement from classical to vernacular grammar, the role of periodicals in commodifying vernacular education and debates about women's education.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".