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Record W7074747158

The Friulian-Canadian Immigrant Experience

2016· article· it· W7074747158 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2016
Typearticle
Languageit
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationDisplacement (psychology)VoiceEthnic group
DOInot available

Abstract

fetched live from OpenAlex

This essay reconstructs the Friulian immigrant experience to Canada through the works of some Friulian and Julian-Dalmatian writers. It highlights how while voicing the deep sense of loss that Friulians feel for their homeland, these texts also prompt a reconciliation with displacement and a reconfiguration of the idea of home which can include multiple belongings. It also analyses how these texts employ different languages, including Friulian, as a strategy of historical reappropriation of the immigrant experience and of renegotiation of identity.L’esperienza migrante dei friulano-canadesiL’articolo ricostruisce la storia dell’emigrazione friulana in Canada attraverso un’analisi di alcune opere di scrittori friulani e giuliano-dalmati. Oltre a dare voce al persistente dolore che affligge i friulani per la perdita della propria patria, questi testi evidenziano anche la necessità di superare il trauma della dislocazione e ridefinire i concetti di patria e appartenenza. Si analizza inoltre come l’uso di diverse lingue, tra cui il friulano, costituisca una strategia di riappropriazione storica dell’esperienza migrante e di rinegoziazione identitaria.

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)0.003
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: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0540.014
Scholarly communication0.0080.002
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.004
GPT teacher head0.209
Teacher spread0.205 · 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
Published2016
Admission routes1
Has abstractyes

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