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Record W1674705229 · doi:10.5325/chaucerrev.48.3.0258

“Save oure tonges difference”:

2014· article· en· W1674705229 on OpenAlexaff
Kara Gaston

Bibliographic record

VenueThe Chaucer Review · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval Literature and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVernacularAlterityLexiconSyntaxContext (archaeology)LiteraturePoetryLinguisticsHistoryPhilosophyArtEpistemology

Abstract

fetched live from OpenAlex

Abstract This article considers the relationship between translation and historical alterity in Troilus and Criseyde. Chaucer opens Book II of Troilus by admitting that the customs of the poem's ancient lovers might seem strange: culture, like language, changes over the centuries. This passage probably derives from Dante's Convivio, which argues that 1,000 years of linguistic change would render the vernacular of one's own city strange and foreign. In order to understand how such alterity can emerge in a translation like Troilus, this article considers Convivio's statements in the context of fourteenth-century Italian vernacular translations that emulate the syntax and lexicon of Latin source texts. These translations expand the expressive range of the vernacular, allowing linguistic change to be glimpsed as it happens. Similarly, in Troilus Chaucer exploits the transformative potential of translation, using close translation to create effects of linguistic—and hence historical—difference within his own lexicon.

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: none
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.007
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.043
GPT teacher head0.238
Teacher spread0.195 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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