Irredentist Propaganda “Baedeker Style:” Anna Franchi’s and Willy Dias’ Nationalist Geographical Fantasy
Bibliographic record
Abstract
This article analyzes how Anna Franchi and Willy Dias (Fortuna Morpurgo) utilized the language of tourism in their irredentist writings during the first two years of World War I. I look at how they adopted specific features of travel guidebooks to create a nationalistic geographical fantasy. I argue that the two authors’ similar approaches have the same two-fold goal: to teach about the geography, history, and even the existence of the contended areas; to induce their readers to “imagine” the nation (in Benedict Anderson’s terms) as a community ideally united, within and beyond the state’s borders, by a common cultural, linguistic, geographical and ethnic heritage. Inspired by Risorgimento ideology and by irredentist historians, Dias and Franchi rooted such heritage in Greek and Roman history and myth and in the Venetian identity of the contended lands. I show how, through discursive strategies of inclusion/exclusion, Dias and Franchi represented the Mediterranean civilization as antithetic to German and Slavic “barbarism.” Drawing upon the work of historians of the Adriatic Littoral, I place Dias’ and Franchi’s works in the broader context of the history of the representation of the contended provinces in irredentist discourse. Through the lens of the Sociology of Tourism, and the Semiotics of Tourism I look at how the two authors produced an ideologized vision of landscape.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".