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Record W4312548187 · doi:10.33137/ic.v31i.39179

Italiese as a Literary Language (The Example of Le maschere laurenziane)

2022· article· en· W4312548187 on OpenAlexaffvenue
Paul Colilli, Diana Iuele-Colilli

Bibliographic record

VenueItalian Canadiana · 2022
Typearticle
Languageen
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsLaurentian University
Fundersnot available
KeywordsLinguisticsLiterary languagePhilosophyLiteratureHistoryArt

Abstract

fetched live from OpenAlex

Born to an Italian American father and an African American mother, Kym Ragusa explores in all her work the private and public impact of being in-between. Given Kym Ragusa's own complex identity, she represents a multilayered experience of diaspora that challenges the American and Italian concepts of Italianness and Africanness. Through her memoir The Skin between Us, Ragusa moves borders, rethinks the limits previously considered fixed and impassable and also puts into discussion the concept of color and race. The Skin between Us revolves precisely around the distance separating her two communities of belonging. Ragusa's memoir questions the notion of identity and belonging and mirrors the quest of the writer to find a crossroad where her Africanness and Italianness can meet. This paper first analyzes the affinities that Ragusa's communities of belonging share, illustrating the many passages, in the memoir, where African American and Italian American representation overlaps. The discussion then pivots to how Sicily represents the connector of her ethnic backgrounds and becomes the paradigm of every border in the world where double culture and ethnicity contaminate each other. In the end, Ragusa bridges the gap between her ethnic identities and discovers that her multiracial background is a valuable quality she has to protect.

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)0.000
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 score0.739
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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