Italiani Brava Gente? The Italian occupation of southeastern France in the Second World War, 1940-1943
Bibliographic record
Abstract
Many academic works have focused on the German occupation of France in the Second World War, both from the perspective of the occupiers and the occupied. Only a few monographs however had dealt so far with the Italian military occupation of southeastern France between 1940 and 1943. My dissertation strives to fill this historiographical gap, by analyzing the Italian occupation policy established by both Italian civilian and military authorities. Compared to the German occupation policy, the Italian occupation was considerably more lenient, as no massacres were perpetrated and wanton violence was rare. In fact, the Italian occupation of France contrasts sharply with the occupation in the Balkans, where Italians resorted to brutal retaliation in response to guerilla activities. Indeed, softer measures in France stemmed from pragmatic reasons, as the Italian army had not the manpower to implement a draconian occupation, but also due to an humanitarian mindset, especially with regards to the Jewish population in southeastern France. This work endeavors to examine the occupation and its impact on southeastern France, especially at a grassroots level, with a particular emphasis on the relations between the Italian soldiers and the Italian immigrants in the area. Furthermore, much light will be shed on the conflict opposing French officials to Italian ones, and on the differences in policy between Italian civilian authorities and Italian military officials.
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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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".