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Record W2550308730 · doi:10.1386/jicms.5.1.47_1

Léolo’s fantasized Italy: Family romance and accented cinema in Quebec

2016· article· en· W2550308730 on OpenAlexaffabout
Kester Dyer

Bibliographic record

VenueJournal of Italian Cinema and Media Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsConcordia University
Fundersnot available
KeywordsMovie theaterAmbivalenceColonialismRomanceContext (archaeology)IndigenousNationalismGender studiesSociologyTrope (literature)AnthropologyAestheticsHistoryPoliticsLiteratureArtPolitical scienceArt historyPsychoanalysisPsychologyLaw

Abstract

fetched live from OpenAlex

Abstract Although directed by a Francophone Québécois film-maker, Jean-Claude Lauzon’s Léolo (1992) presents a cinematic treatment of Italy that foregrounds exile as theorized by Hamid Naficy’s concept of ‘accented cinema’. Léolo also recasts the family romance trope, which Heinz Weinmann highlights as central to Quebec cinema. Meanwhile, commentators have stressed the deeply political dimensions of Léolo despite Lauzon’s disavowal of any nationalist intent. This film consequently provides insights into the ambivalent role of Italians in Quebec’s struggle to confront the challenges posed by immigration and by its own colonial history. The current article therefore explores Léolo through a framework combining accented cinema and the family romance, and juxtaposes this text with Caffè Italia Montréal, a film which epitomizes accentedness in the context of Quebec’s Italian community. This analysis thus reveals how, in Léolo, a cinematically unasserted Indigenous influence intertwines with overtly fantasized Italianness to complicate Lauzon’s position on national identity. In so doing, this article comes to affirm the centrality of Indigenous concerns for grasping intercultural relationships whether formed through colonialism or contemporary immigration.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.831
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.285
Teacher spread0.259 · 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 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
Published2016
Admission routes2
Has abstractyes

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