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Untold Stories of Loss: Mourning the ‘Enemy’ in Second World War Britain

2015· article· en· W1998750513 on OpenAlexaboutno aff
Wendy Ugolini

Bibliographic record

VenueJournal of War and Culture Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsnot available
Fundersnot available
KeywordsAdversaryDeclarationTragedy (event)Context (archaeology)NarrativeHistoryImmigrationMemorializationGender studiesCriminologyPolitical scienceSociologyLawLiteratureArtArchaeologySocial science

Abstract

fetched live from OpenAlex

Italy's declaration of war on Britain in June 1940 had dramatic consequences for Italian immigrant families living within Britain, signalling their traumatic construction as the ‘enemy within’. Male Italians between the ages of sixteen and seventy who had been resident in Britain for less than twenty years and all those who had been identified by MI5 as members of Italian Fascist clubs were interned, with those categorized as the ‘most dangerous’ internees deported overseas. Tragedy struck when a ship transporting internees to Canada, the Arandora Star, was torpedoed killing over 800 people, including over 400 Italians. This article explores the ways in which the disaster was recalled within the personal narratives of descendants of the victims, reflecting upon how bereaved families endured their loss within a wider context of wartime anti-Italianism and how aspects of the grieving process remained unresolved through the subsequent decades. It also reflects upon the increasing memorialization of the disaster, which intensified after the interviews had taken place, and its implication for the author, as a historian working with personal testimonies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.320
Teacher spread0.286 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2015
Admission routes1
Has abstractyes

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