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Record W3197843275 · doi:10.24043/isj.172

Cainà: Islandscape and ‘islanderscope’ on screen

2021· article· en· W3197843275 on OpenAlexvenueno aff
Myriam Mereu, Daniele Gavelli

Bibliographic record

VenueIsland Studies Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsCharacter (mathematics)Agency (philosophy)Identity (music)Symbol (formal)Representation (politics)Pacific islandersAllegoryAestheticsSociologyEthnologyHistoryGenealogyArtArt historyAnthropologyPhilosophyPolitical sciencePoliticsLawSocial scienceLinguistics

Abstract

fetched live from OpenAlex

The establishment of Island Studies within the academe and the introduction of concepts such as ‘islandness’ and ‘islandscape’ have accompanied a general rethinking of the concept of insularity which encompasses the reflection over a cinematic representation of islands and islanders. The use of islands as cinematic landscapes and settings has reinforced cultural, mythical, and identity stereotypes associated with the island imagery built-up in literature, as well as the construction of the islander as a character exhibiting specific behavioural features. The film Cainà. L’isola e il continente (Gennaro Righelli, 1922) is emblematic insofar as it is the first feature film shot in Sardinia and its character is not just a symbol of feminine rebellion against a patriarchal society, but it also serves as an allegory of an unspoiled island, such as it was considered and depicted at that time. As islanders ourselves, we have wondered to what extent Cainà adheres to the stereotypes of islandness and insularity conventionally ascribed to islands and, in this specific case, to Sardinia. Our paper aims to examine the genesis of the Sardinian insular imagination through the lens of the cinematic construction of ‘islanderness’ and ‘islanderscope’, an assortment of agency representing islanders — and islands — on screen.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score0.999

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 studies0.0030.000
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 head0.050
GPT teacher head0.351
Teacher spread0.302 · 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.

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
Published2021
Admission routes1
Has abstractyes

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