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Record W2540749655 · doi:10.33137/q.i..v36i2.26898

Elementi di plurilinguismo nell’opera di Filippo Orioles

2016· article· it· W2540749655 on OpenAlexvenueno aff
Salvatore Bancheri

Bibliographic record

VenueQuaderni d italianistica · 2016
Typearticle
Languageit
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La prima metà del Settecento — periodo in cui scrisse Filippo Orioles (1687–1793), autore del Riscatto d’Adamo — fu segnato in Sicilia da un continuo alternarsi di dominazioni e quindi anche da normale commistione di linguaggi. Di riflesso, i lavori dell’Orioles (La notte in giorno, La S. Rosalia, Il S. Alessio e Il San Basilio Magno), analizzati brevemente nella loro esemplarità linguistica, sono uno specchio di questa realtà. Nelle opere esaminate troviamo una mescolanza di lingue (italiano, spagnolo e latino), frequenti latinismi, dialetti (siciliano e napoletano). La contaminazione dei linguaggi si manifesta sia sul piano puramente linguistico, sia su quello dei codici e delle tradizioni culturali: abbiamo in contempo il linguaggio lirico e drammatico, colto e popolare, profano e religioso. Al linguaggio galante dei salotti si contrappone il dialetto schietto dei popolani; al tono epico si contrappone quello eroicomico dei servi. L’elemento più interessante delle commedie agiografiche dell’autore palermitano è il plurilinguismo — inteso in senso lato — grazie al quale va in scena, sia pure in modo anacronistico, la Sicilia del ’700, sia aristocratica che popolana. E sono proprio, e principalmente, i personaggi del popolo con il loro colorito dialetto che rendono meno pesanti, se non addirittura vivaci, le commedie dell’Orioles.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.006

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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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