‘So she has been educated by a vulgar, silly, conceited French governess!’ Social anxieties, satirical portraits, and the eighteenth‐century French instructor
Bibliographic record
Abstract
Maria Edgeworth’s pedagogical short stories ‘Mademoiselle Panache’ (1800, 1801) and ‘The Good French Governess’ (1801) portray contrasting French instructors, and illustrate a transformation in English girls’ education in French at the end of the eighteenth century. While ‘Mademoiselle Panache’ looks back to the disingenuous French instructors of eighteenth‐century comedy, demonstrating English anxieties about the supposedly corrupting influence of the French on young girls, ‘The Good French Governess’ shows the positive influence of French émigrés in late eighteenth‐century French instruction. In contrast to critical assumptions that the English public’s outraged response to the French Revolution terminated English interest in all things French, these and other contemporary texts show that English girls’ education in French was not diminished by anti‐Jacobin attitudes, and indeed flourished into the nineteenth century.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".