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Record W2760167560 · doi:10.7202/1041031ar

Packaging a Chinese “Beauty Writer”: Re-reading Shanghai Baby in a Web Context

2017· article· en· W2760167560 on OpenAlexvenueno aff
Liu Bin, Brian James Baer

Bibliographic record

VenueMeta Journal des traducteurs · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBeautyContext (archaeology)ChinaReading (process)PoliticsSociologyGender studiesCommunismLiteratureMedia studiesAestheticsHistoryArtPolitical scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Based on a comparative discourse analysis of the 2001 English translation of the pioneering “beauty writer” Wei Hui’s semi-autobiographical novel Shanghai Baby and the original Chinese work (1999), this paper aims to demonstrate how the reception of non-specialist readers in the form of online book reviews is influenced by the politics of reception in the Western world as well as the translational shifts in the text. Building the investigation upon the nineteenth-century sinologist translation model that packages Chinese culture as clichéd Chineseness in addition to the Western reception model that packages Chinese women as reckless lovers and escapees from communist despotism, the study argues that largely subject to the stereotypical expectations of Western readers about the Third World culture and women, the shifts reinforcing the prevalent stereotypes in the translation overshadow the author’s original intention of speaking for a small tribe of young people exploring their unorthodox existence in China. Lastly, the study concludes with the affirmation of Shanghai Baby ’s social impact on both host and source culture in an attempt to relate its significance to a global context.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.341
Teacher spread0.284 · 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 designObservational
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

Citations10
Published2017
Admission routes1
Has abstractyes

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