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Record W4323660724 · doi:10.33137/ic.v20i.40115

She is My Motherland: il viaggio in Sicilia di Venera Fazio e Delia De Santis

2023· article· it· W4323660724 on OpenAlexaffvenue
Paolo Chirumbolo

Bibliographic record

VenueItalian Canadiana · 2023
Typearticle
Languageit
FieldArts and Humanities
TopicItalian Literature and Culture
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGeologyHumanitiesArt

Abstract

fetched live from OpenAlex

Pubblicata nel 2004 dalla casa editrice Legas, l'antologia Sweet Lemons: Writings with a Sicilian Accent edita da Venera Fazio e Delia De Santis rappresenta il primo tentativo di raccogliere in un unico volume testi e testimonianze di scrittori siciliani che, in modo diverso, fanno i conti con il proprio displacement e il proprio destino di emigranti.Lungi dall'essere omogeneo e organico, Sweet Lemons è un volume che si contraddistingue per la sua multiformità e in cui il lettore si trova a passare dalla prosa alla poesia al teatro con grande disinvoltura.È questo, del resto, uno degli scopi delle curatrici, come spiega Venera Fazio nell'introduzione:To highlight the diversity of talent and the complexity of Sicilian culture and immigrant experiences, Delia and I included a range of writing genres: short stories, poems, essays, memoirs, legends, folk tales, plays, book excerpts, and one film script.( 16)

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.957
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.219
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes2
Has abstractyes

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