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Record W2158148622 · doi:10.7202/037153ar

Poets of Bifurcated Tongues, or on the Plurilingualism of Canadian-Hungarian Poets

2007· article· en· W2158148622 on OpenAlexvenueaboutno aff
Katalin Kürtösi

Bibliographic record

VenueTTR traduction terminologie rédaction · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryNeuroscience of multilingualismLinguisticsTheme (computing)Code-switchingReflexivityLiteratureSociologyHistoryArtPhilosophyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Poets of Bifurcated Tongues, or on the plurilingualism of Canadian-Hungarian Poets — This article aims at an analysis of the plurilingualism of four poets of Hungarian origin, living in Canada: Robert Zend, George Vitéz, László Kemenes Géfin and Endre Farkas. Before examining the poems themselves, the various concepts of plurilingualism and the aspects of grouping these poems, including the code-switching strategies used in them, are reviewed. The base language and the nature of code-switching is discussed with a special emphasis on the relationship of grammatical units, intra- and intersentential switches within contexts where plurilingualism occurs. The first three poets have become bilinguals as adults: they form part of Hungarian literature as well as of Canadian writing. The last one, however, has a childhood bilingualism and is considered an English-Canadian Poet. Since they have a twofold minority status (Hungarian origins, plus writing in English in Montréal), analysis of these poets requires a special approach. The main hypothesis of the article is that, when using more than one language within the same work, the author is able to reach special effects which would be otherwise impossible. These poems, plurilingual in nature, also show that, for these authors, language is of multiple use: not only is language a tool of communication, but also the theme of some of their poems: they are often self-reflexive, making formal and semantic experimentation possible.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.128
GPT teacher head0.281
Teacher spread0.153 · 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 designQualitative
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
Published2007
Admission routes2
Has abstractyes

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