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Asian Diasporic Narratives of Return

2019· reference-entry· en· W2981625180 on OpenAlexaboutno aff
Patricia P. Chu

Bibliographic record

VenueOxford Research Encyclopedia of Literature · 2019
Typereference-entry
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeHomelandGender studiesContext (archaeology)HistoryMemoirSociologyLiteraturePolitical scienceArtPoliticsArt history

Abstract

fetched live from OpenAlex

Abstract The plot of return from America to Asia to search for origins is central to Asian diasporic literature of the past 120 years. By returning to Asia and writing about their ancestors, Asian North Americans (those born or raised in the United States or Canada) expand their cultural understanding and produce narratives that serve as “countermemory,” contributing to a communal memory that is “oppositional . . . the memory of the subordinated and the marginalized, memory from below versus memory from above,” in the words of Viet Thanh Nguyen. For immigrants and their offspring, Asian diasporic narratives of return typically reflect experiences of “racial melancholia,” described as unresolved mourning for the losses associated with migration, in the context of social discrimination, exclusion, or marginalization due to race. For Asians, racial melancholia is exacerbated by its incompatibility with ideals of America as equal, inclusive, and race-blind. Writers sometimes use narratives of return to comprehend and resolve their parents’ melancholia by remembering their stories and articulating their grievances; this process of countermemory typically requires a lengthy cultural apprenticeship. In addition to family histories, narratives of return encompass essays, memoirs, novels, poems, plays, and films. They may also be written by or about protagonists born and raised in Asia who return, perhaps to reform or improve their homeland, after living abroad.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.030
GPT teacher head0.349
Teacher spread0.320 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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