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Record W4382243878 · doi:10.54103/2037-3597/20377

PARALLELISMI E DISCONTINUITÀ IN DUE CONTESTI ANGLOFONI

2023· article· it· W4382243878 on OpenAlexaboutno aff
Margherita Di Salvo

Bibliographic record

VenueItaliano LinguaDue · 2023
Typearticle
Languageit
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesStudioRepertoireSociologyArtVisual artsLiterature

Abstract

fetched live from OpenAlex

Questo contributo descrive i repertori linguistici degli italiani migrati stanziati a Toronto (Canada) e a Londra (Regno Unito); propone di mostrare la loro evoluzione nel corso delle diverse ondate migratorie, in modo da individuare somiglianze e divergenze tra i flussi degli anni Cinquanta e Sessanta e le migrazioni contemporanee. In tale prospettiva, obiettivo ultimo del contributo è evidenziare la criticità della nozione di heritage langauge così come applicata allo studio delle comunità italiane nel mondo e di suggerire modelli di lettura alternativi basati al concetto di repertorio linguistico.
 
 Parallelisms and discontinuities in two anglophone contexts
 This paper focuses on the linguistic repertoires of Italian migrants settled in two different cities, that are Toronto (in Canada) and London (in the UK). It aims to show their evolution during the various migratory waves and to identify similarities and differences between the flows that took place in the Fifties and in the Sixties and those that started after the recent crisis. The ultimate goal of the paper is to highlight the critical points of the heritage language approach as applied to the study of Italian communities worldwide: the paper aims of discuss alternative approaches based on the notion of linguistic multiple repertoire that has been recently proposed by several authors.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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