Designing Truth between Manuscript and Publication: The Eighteenth-Century French Vision of Peru in Marmontel’s <i>Les Incas</i> (1777)
Bibliographic record
Abstract
This essay interrogates the tensions between historical fact and colonial fiction in Jean-François Marmontel’s Les Incas, ou le destruction de l’Empire du Pérou (1777). Through this study of deleted passages and publisher notes in the 1776 manuscript of the novel (Houghton Library, Harvard University), Marmontel’s concern with verisimilitude, truth, and objective reality belies the fantasy of conquest and the myths of American Indigeneity that are central to eighteenth-century French understandings and imaginings of the Inca Empire and the American continent as a whole. Politically, the novel served a dual purpose: to vehemently denounce the Spanish conquest of the Americas and to subversively critique the “fanaticism” of the ancien régime in the years leading up the 1789 Revolution. Across the Atlantic, the novel was read by generals of the Latin American Wars of Independence, and it shifted from an allegorical text to a direct call for revolution. Despite Marmontel’s aim of creating a philosophical and historical novel, Les Incas perpetuates the hegemonies and hierarchies of colonialism, falling back onto well-established tropes. In choosing what was considered in Europe as “exotic” as a vehicle for political critique, Les Incas maintains and reinforces the very systems against which the revolutionaries of the late eighteenth century fought.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".