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Record W337303334 · doi:10.3138/cjh.47.2.355

June 1940: The Italian Army and the Battle of the Alps

2012· article· en· W337303334 on OpenAlexvenueno aff
Emanuele Sica

Bibliographic record

VenueJournal of History · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsnot available
Fundersnot available
KeywordsBattleGermanPolitical scienceAncient historyArchaeologyEconomic historyGeographyHistory

Abstract

fetched live from OpenAlex

This article focuses on the “Battle of the Alps” of June 1940, which pitted the Italian Regio Esercito against the French Armée des Alpes. Fearing that an early capitulation of France to the German invasion that had begun in May would prevent Italy from sharing the spoils of victory, Mussolini ordered an offensive against France on 15 June 1940. Despite the battle raging in the north, the French Army successfully repelled the attacking force and the Italian assault petered out after a few days, with no significant victories and few territorial gains. Aside from the difficulties of crossing the Alpine mountain range, a geographical feature the French had strongly fortified, the Italian campaign was hindered by poor strategy, ineffective tactics, an outdated military doctrine that failed to acknowledge the importance of combined arms warfare, and appallingly inadequate materiel owing to the erosion of the Italian military industrial base in the 1930s. In fact, the Battle of the Alps set the tone for the overall disappointing military campaign of the Regio Esercito in the Second World War, as the Italian army never fully recovered from its dismal start.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0050.001
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.017
GPT teacher head0.245
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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