The Gender of Pseudotranslation in the Works of Marie-Jeanne Riccoboni, Mme Beccari and Cornélie Wouters
Bibliographic record
Abstract
While authorship recognition was a challenge for all eighteenth-century aspiring writers regardless of their gender, the social position of women was such that public claims of authorship and ownership over a text were even less self-evident in the public sphere. As will be illustrated in this article, female writers especially made extensive use of transfer strategies (such as translation and pseudotranslation) to establish their authorship, thereby turning paratext and narrative into a dynamic maneuvering space. Considered from a gender perspective, the challenge for eighteenth-century female writers was to gradually “invent” themselves, or rather establish a voice of their own. Taking on a different (cultural) persona—even if only on a paratextual level—could provide them with a discursive “platform” from which they could negotiate their way into the literary field. In order to illustrate this gender-specific emancipatory quality of pseudotranslation, as established mainly in their paratexts, the present article proposes a comparative analysis of their forms and functions in the career and oeuvre of three eighteenth-century French women writers, Marie-Jeanne Riccoboni, Mme Beccari and Cornélie de Wouters, who all made extensive use of pseudo-English fiction.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".