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Record W4230510990 · doi:10.3138/cras.2013.004

Rhetoric of Wounds: Trauma, Identity, and Interpersonal Relationships in Chuang Hua's <i>Crossings</i>

2013· article· en· W4230510990 on OpenAlexvenueno aff
Natalie Nadon

Bibliographic record

VenueCanadian Review of American Studies · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature, Magical Realism, García Márquez
Canadian institutionsnot available
Fundersnot available
KeywordsRhetoricIdentity (music)ChinaInterpersonal communicationInterpersonal relationshipLiteratureAestheticsPsychoanalysisPsychologySociologyHistoryGender studiesSocial psychologyArtPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Abstract: Chuang Hua's Crossings is a novel that reflects the pressures on individuals and families as they struggle to make a life for themselves in exile, both literally and metaphorically. As the protagonist, Fourth Jane's own emotional and psychological wounds reflect those of her Chinese-American Family, as they attempt to find a sense of stability and cultural identity in spite of being displaced from China, their home, and their culture. Each in their own way, the characters of Crossings try to reconcile their prescribed roles within traditional Chinese culture, with their changing lives and surroundings in Europe and America. The medical imagery, as well as the images of blood and wounds in the text, reflect this need for stability and healing. The characters of Fourth Jane, Dyadya, and Ngmah frequently employ the comforting familiarity of medicine, traditions, and rituals to heal their inner wounds and find a sense of belonging.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0080.012
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.062
GPT teacher head0.302
Teacher spread0.240 · 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
Published2013
Admission routes1
Has abstractyes

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