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Record W4310495744 · doi:10.5539/ijel.v13n1p65

Gender Reconstruction in Chinese Ci When Translated into English

2022· article· en· W4310495744 on OpenAlexvenueno aff
Wang Ying

Bibliographic record

VenueInternational Journal of English Linguistics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsnot available
Fundersnot available
KeywordsLyricsContext (archaeology)Value (mathematics)LinguisticsPower (physics)Critical discourse analysisPsychologySociologyGender studiesLiteratureHistoryComputer sciencePolitical scienceArtPhilosophyPoliticsLaw

Abstract

fetched live from OpenAlex

This paper aims to study how gender in ci (Song lyrics) written by Li Qingzhao in the Song Dynasty is reconstructed in the process of translation. By analyzing the discourse practice of gender construction in traditional Chinese culture and its reconstruction in translation, it is hoped that different powers and values will be revealed through Critical Discourse Analysis (CDA) and Systemic Functional Linguistics (SFL). It is found that the reconstruction of gender in Chinese ci-a high-context original text-is an attempt to connect genders with social practices and also a gender doing performance negotiated between different power, and value systems.

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)0.001
metaresearch head score (Gemma)0.057
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.057
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.317
Teacher spread0.298 · 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 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
Published2022
Admission routes1
Has abstractyes

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