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Record W4411039283 · doi:10.1017/9781108556828.005

Competition, Retranslation and Travesty

2025· book-chapter· en· W4411039283 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2025
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCompetition (biology)Biology

Abstract

fetched live from OpenAlex

The topic of competition starts with translators’ incorporation of others’ versions into their own texts, then moves on to translators’ prefaces where they situate themselves in relation to particular predecessors, such as Leopardi’s relationship with Caro’s sixteenth-century Eneide . I examine in depth the self-positioning and self-fashioning in the paratexts in the English tradition of Aeneid translations from Caxton down to Wordsworth. The second section deals with the phenomenon of ‘retranslation’, which has two manifestations: when translators lift elements from preceding translations and when they revisit their own earlier versions and modify them. Then I consider competition with Virgil himself, starting with the challenge to Paul Valéry to translate the Eclogues . The chapter concludes with brief consideration of parody and travesty of Virgil as special forms of retranslation, with examples from a seventeenth-century Dutch collaboration on the Eclogues , a seventeenth-century parody of Eclogue 1 by an Irishman and an eighteenth-century travesty of the Aeneid in German.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.991
Threshold uncertainty score1.000

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 head0.022
GPT teacher head0.175
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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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