Bibliographic record
Abstract
This thesis examines the early modern debates surrounding the incorporation of French loan words into the English vocabulary through an analysis of the prefaces of a variety of early modern English dictionaries and a selection of Restoration plays, political pamphlets and tracts.It considers the long seventeenth century, starting with Robert Cawdrey's dictionary of 'hard words', A table alphabeticall (1604) and ending with Samuel Johnson's A Dictionary of the English Language (1755).The thesis is not concerned with whether particular words are in fact French loans, nor with the chronology of their usage, but rather examines the debates surrounding linguistic borrowing identified as French by contemporaries.Neither is the emphasis on the actual words themselves, as much as on the attitudes towards their use and the portrayal of those that use them.The thesis analyses the representation of French linguistic borrowing in three domains of discourse (dictionaries, Restoration satire, political pamphlets and periodical essays), paying particular attention to the metaphors and images that are employed in these representations.Taking into consideration ideas of linguistic purism and language corruption, it explores how representations of French borrowing can be situated within a larger historical context of English nation building and fluctuating Anglo-French relations.a named human population sharing an historic territory, common myths and historical memories, a mass, public culture, a common economy and common legal rights and duties for all members 44 Like Hadfield, Grabes emphasises the role of writing in the construction of national identity, arguing that: 41 Ian Lancashire, 'Introduction to Lexicons of Early Modern English', http://leme.library.utoronto.ca/public/intro.cfm42 Ian Lancashire, 'Introduction to Lexicons of Early Modern English', http://leme.library.utoronto.ca/public/intro.cfm;
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".