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Record W2767820570 · doi:10.3968/9853

Relocation of Cultural Identity in Tripmaster Monkey: His Fake Book

2017· article· en· W2767820570 on OpenAlexvenueno aff
Limin Shen, Ruwen Zhang

Bibliographic record

VenueStudies in literature and language · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsChinese americansIdentity (music)ProsperityVariety (cybernetics)PerplexityRelocationReading (process)Identity crisisSociologyCultural identityLiteratureHistoryAestheticsMedia studiesAnthropologyLawArtEthnic groupPolitical scienceSocial scienceFace (sociological concept)

Abstract

fetched live from OpenAlex

Maxine Hong Kingston, born in California, America in 1940, is a celebrated Chinese-American writer. And she is the most representative female writer in promoting the prosperity of Chinese-American literature in the late 20 century. As a Chinese American writer’s unique identity, she pays special attention to Chinese-Americans in her works. Tripmaster Monkey: His Fake Book is her first real novel published in 1989. Its publication brought strong social shock and numerous literary critics and scholars to evaluate her works from different perspectives in a variety of literary theory. Unlike her previous works, Tripmaster Monkey: His Fake Book transfers the focus from the reconstruction of Chinese-American history to the Chinese American cultural identity. Through careful reading of the text, this paper, with Homi K. Bhabha’s post-colonial theory as a theoretical base, aims to explore the reconstruction and relocation of cultural identity after cultural perplexity and disillusionment, trying to open up a new way out for Chinese-Americans.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.375
Teacher spread0.355 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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