MétaCan
Menu
Back to cohort
Record W3048378404 · doi:10.21992/tc29484

“Once, Twice and Again!” Kipling’s Works in the Russian Twentieth Century Retranslations

2020· article· en· W3048378404 on OpenAlexvenueno aff
Natalia Kamovnikova

Bibliographic record

VenueTranscUlturAl A Journal of Translation and Cultural Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicBorges, Kipling, and Jewish Identity
Canadian institutionsnot available
Fundersnot available
KeywordsJunglePoetryPoliticsOrder (exchange)MythologyLiteratureAudience measurementRussian cultureRussian literatureHistoryEmpireContext (archaeology)ArtArt historyPolitical scienceLawAncient history

Abstract

fetched live from OpenAlex

The article traces the evolution of the image of Rudyard Kipling and of the role his works played in the Russian literature and culture. The study is performed on the material of Russian retranslations of Kipling’s poetry and of The Jungle Book, which followed different patterns and contributed differently and at times even dissonantly to the construction of the image of Kipling and his literary legacy in the Soviet Union. Strong competition of big independent publishers in the Russian Empire ensured multiple retranslations of The Jungle Book in order to cater for the demands of the wide readership. The change in political powers in 1917, the nationalization of print, and the focus on education worked towards the development of a very selective approach to the rendering of The Jungle Book, which eventually reduced itself to recycling a limited number of episodes. By contrast, Kipling’s poetry translation took the form of pioneering work, especially in the context of the ban on Kipling in the 1930 – 1970s. These two opposite vectors that Kipling’s translations took in the twentieth century had a tangible effect on the perception of Kipling as an author and inspired the Russian art of the second part of the twentieth century in the fields of literature, music, and film.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.438

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.114
GPT teacher head0.292
Teacher spread0.177 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueTranscUlturAl A Journal of Translation and Cultural StudiesSame topicBorges, Kipling, and Jewish IdentityFrench-language works237,207