The Cultural Politics of Translation: The Case of Voltaire’s Mérope and Scipione Maffei’s Merope
Bibliographic record
Abstract
In 1743, Voltaire writes to Scipione Maffei his intention to translate Merope, a drama the Italian playwright had composed thirty years before and that Voltaire deemed worthy of the French stage due to its treatment of the classic heroine and its adherence to classical norms. However, Voltaire later claims that due to flaws in Maffei’s work, he will write his own version of the play. This petty incident stirred a long-lived and animated debate over which dramatist had adhered more closely to the principles of classical theatre and whose country could claim its primacy in European theatre. In my paper, I use this episode to illustrate how translation shapes and is shaped by source and target cultures, and how it determines what is peripheral and what is central to intercultural debates. I argue that both Voltaire and Maffei struggle to assert their position as leading “translators” of classical Greek theatre and eminent interlocutors in the debate over form and content of modern drama. My paper will use Voltaire’s translational faux pas to reflect on the larger issues of how translation situates itself in the middle of cultural hierarchies and how it fashions national identity, cultural pertinence, national subordination, and notions of cultural peripheries and centers, all topics that lie at the heart of contemporary translation studies
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.067 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".