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Record W2464666569 · doi:10.1386/jicms.4.3.353_1

Stolen bicycles and exploited children: Italian cinema and its relation to the cinema of independent India (1947–1977)

2016· article· en· W2464666569 on OpenAlexaff
Carlo Coen

Bibliographic record

VenueJournal of Italian Cinema and Media Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsYork University
Fundersnot available
KeywordsMovie theaterRealismIdeologyIntertextualityPartition (number theory)AestheticsRelation (database)PoliticsHistorySociologyLiteratureMedia studiesArtPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract The years that follow the end of World War II mark a unique historical-political situation shared by India and Italy. The debate in both nations looks at cinematic neo-realism as the regenerating force capable of leading towards a renewed cultural life after the events of decolonization and partition on the one side, and the disasters of fascism and the destructions of the war on the other. Neo-realism is seen as the best possible choice for intellectuals and film-makers in both countries. The new role of the artist suggested by the works of Italian neo-realism (especially Bicycle Thieves [De Sica, 1948]) is perceived by Indian intellectuals as the right solution for the renewal. This article searches for references and stylistic echoes found in the complex body of Indian cinema. The methodological approach of the article, therefore, relies both on intertextuality and on the analysis of some writings where one finds reference to views and concepts on cinema clearly inspired by the strategies and the ideology of Italian neo-realism.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.025
GPT teacher head0.291
Teacher spread0.266 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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