Maps, Painting and Lies Portraying Napoleon's Battlefields in Northern Italy
Bibliographic record
Abstract
A comparison of Giuseppe Bagetti's landscape sketches, watercolours, oil paintings and engravings with contemporary maps and the existing landscape reveals that in the creation of Bagetti's landscapes, narrative played a role that differed in cartographic and artistic representations. The comparison also demonstrates that his images were powerful constructions that were more successful in reflecting a narrative of glorious conquest than was possible through cartography. This paper offers a critical examination of Bagetti's representations of Napoleon's northern Italian campaign, which he sketched and painted between 1802 and 1809. Bagetti's paintings were neither pacifist nor an expression of Piedmontese patriotism but instead were inspired by, and constructed according to, a narrative about the conquest that reflected the views of the French authorities. The narrative found expression in formal written instructions from the central cartographical office in the Dépôt de la guerre, Paris, in verbal and written instructions from Bagetti's immediate superior, Jean François Martinel, and in letters personally addressed to Bagetti from the officer commanding the Dépôt. It is clear from a careful reading of the correspondence and from a comparison of Bagetti's paintings with both the present landscape and maps made at the time that Bagetti's disputes with his supervisors revolved around protecting his artistic integrity and reputation rather than resisting the authority of a foreign regime.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".