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Transnationalism Undermining the Canon: A Close and Distant Reading of Several Transatlantic Literary Networks in Translation

2021· article· en· W3217208875 on OpenAlexaboutno aff
Raluca Tanasescu

Bibliographic record

VenueBelas Infiéis · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

This essay argues that random acts of poetry translation in transnational context play a significant role in turning any apparently homogenous literary system into a network with many access points. In doing so, they overtly or covertly undermine the idea of a literary canon, since they position, more or less explicitly, such canon against their own literary taste and network of acquaintances. In addition, the lack of financial conditioning makes this kind of translation barters reach literary audiences more easily. Since these exchanges are more commonly initiated by translators working in lesser-known languages, it follows that transnational translation barters level out cultural imbalances by having the translator-poets’ work translated into languages of wider circulation. This contribution presents four kinds of transnational exchanges in Romanian context and argues that more complex translation mechanisms result into a more open, more diverse, and a more dynamic literary scene, in which translators play a prominent role. From a methodological point of view, this essay combines the traditional close reading of the texts and paratexts with quantitative analysis and network visualization to lay out the blueprint of Romanian translations of US and Canadian poetry in periodicals between 2007 and 2017 and quantify the number of random exchanges against a transnational backdrop.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.943
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

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

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 head0.041
GPT teacher head0.261
Teacher spread0.220 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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