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Le «città proibite» di Curzio Malaparte e Alceo Valcini: narrazioni, diffrazioni e rinegoziazioni letterarie del ghetto di Varsavia in due scrittori italiani del dopoguerra

2020· article· it· W3033026162 on OpenAlexaff
Tommaso Pepe

Bibliographic record

VenueLaboratoire italien · 2020
Typearticle
Languageit
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsTrinity College
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La mattina del 25 gennaio 1942 Curzio Malaparte, impegnato per Il Corriere della Sera in un lungo reportage giornalistico sul fronte orientale, varca la soglia della «città proibita» di Varsavia. Malaparte fu il primo scrittore italiano a compiere una ricognizione personale del più grande dei ghetti ebraici istituiti in Europa orientale: il resoconto letterario di quella esperienza verrà raccolto in una lunga sequenza narrativa di Kaputt, libro pubblicato nel 1944. Malaparte, tuttavia, non fu solo nella sua visita: infatti ad accompagnarlo fu anche un altro giornalista italiano, Alceo Valcini, la cui figura è integralmente rimossa dal racconto di Kaputt. Corrispondente da Varsavia per conto del Corriere, Valcini avrebbe assistito da testimone oculare all’invasione tedesca del 1939, alla successiva occupazione della città e alla rivolta del ghetto ebraico nella primavera del 1943. Le memorie di quegli eventi confluirono in un volume, Il calvario di Varsavia, edito da Garzanti nel 1945 e mai più ristampato in seguito. Il presente contributo intende proporre una lettura selettiva di queste due atipiche narrazioni del ghetto varsaviano, elaborate da autori la cui parabola intellettuale si rivelò oltretutto profondamente compromessa con l’universo ideologico del fascismo.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.006
Science and technology studies0.0030.002
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

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