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Record W3182228356

한국 젠더 번역 사례 연구 - The Awakening 번역을 중심으로

2015· article· ko· W3182228356 on OpenAlexaboutno aff
마승혜

Bibliographic record

Venue통번역학연구 · 2015
Typearticle
Languageko
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsTranslation (biology)PublishingLinguisticsTranslation studiesSociologyGender studiesPsychologyPolitical scienceLawPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Gender translation in Korea is known to be relatively passive or conservative compared to that in western countries, especiallyCanada. The claim about gender translation in Korea, however, has not yet been substantiated with specific grounds; therefore, this paper first introduces previous cases of feminist translation and strategies employed in feminist translations mostly in Canada and compares them with the detailed expressions and strategies applied in the case of gender translation in Korea. The texts selected for the analysis and comparison are the translations of The Awakening by Kate Chopin, an American feminist writer. A translation carried out under the intention of emphasizing a woman character's challenging spirit or resistance and the other translation that intended to be faithful to the source text are compared thoroughly to shed light on the specific strategies and adjustments in the gender translation. The analysis results substantiate the previous claim that the gender translation in Korea is relatively passive or conservative, which is mostly author-centered rather than translator-centered. Finally this paper seeks to unravel the reasons behind the rather passive and author-centered translation, which are associated with the insufficient pool of readers who are willing to accept radical or aggressive feminist translations and the status of translators in translation for publishing.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.150
GPT teacher head0.304
Teacher spread0.154 · 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 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
Published2015
Admission routes1
Has abstractyes

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