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Record W2624402543 · doi:10.33137/q.i..v37i2.29234

Food Consumption in Ferzan Ozpetek’s <i>Hamam</i> and Luca Guadagnino’s <i>Io sono l’amore</i>: A Gender Issue

2018· article· en· W2624402543 on OpenAlexvenueno aff
Patrizia Sambuco

Bibliographic record

VenueQuaderni d italianistica · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsnot available
Fundersnot available
KeywordsConsumption (sociology)Reading (process)Movie theaterIdentity (music)Food consumptionSociologyGender studiesAestheticsArtLiteraturePsychologyPhilosophyLinguisticsEconomics

Abstract

fetched live from OpenAlex

Within the wide range of scholarly works on food studies, the topic of food and cinema has gained increasing attention in recent years. This article contributes to the discussion offering a gender per­spective in the analysis of Italian films. It examines cinematic represen­tations of food consumption in Ferzan Ozpetek’s Hamam and Luca Guadagnino’s Io sono l’amore. Food consumption is a means of look­ing at self-identity and the relationship of the individual to the outside world. Eating implies taking part of the outside world inside, and as such it involves not only nutrition for the body but invests the sub­ject with cultural meanings. As a result, the analysis of food consump­tion lends itself to an examination of cultural gender dynamics that influence representations. Through a gender reading of specific scenes, the article argues that in spite of the apparent representations of inde­pendent, successful female protagonists who dare to challenge social conventions, the films considered contribute to the reinforcement of traditional gender constructions. Claude Fischler’s and Pasi Falk’s theo­ries of food consumption help to uncover how the sensory and aesthetic dimensions prevail in the representations of the women protagonists of the films analysed. The female protagonists’ relationship to the outside world remains an individual one, experienced at the sensory level, that cannot express the radical and collective transformations available to the male protagonists.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.005

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 head0.032
GPT teacher head0.285
Teacher spread0.252 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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