Between Two Fires? Austro-Hungarian Soldiers of Italian Origin during World War I. Review of: Di Michele, A. (2022). Mezh dvukh mundirov. Italoiazychnye poddannye Avstro-Vengerskoi imperii na Pervoi mirovoi voine i v russkom plenu [Between Two Uniforms. Italian-Speaking Subjects of the Austro-Hungarian Empire in World War I and in Russian Captivity] (M. G. Talalay, Trans. & Ed.). Italiia — Rossia. St Petersburg: Aleteja, 2022. 286 p., ill.
Bibliographic record
Abstract
This review considers the study by A. Di Michele, professor at the Free University of Bolzano (South Tyrol), dedicated to the pre-war and military experience, as well as the experience of captivity of Italian-speaking soldiers of the Austro-Hungarian army during World War I. The main emphasis is placed on its role in the process of their ethno-cultural and ethno-political self-identification, directly related to the population and identity politics pursued by the states of Europe and Russia in the second half of the nineteenth — first quarter of the twentieth centuries. It demonstrates what gaps A. Di Michele’s study is able to fill and what problems to actualise, focusing simultaneously on the regional, national, and supranational contexts of the topic of Austro-Hungarian soldiers of Italian origin during World War I and in Russian captivity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".