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Record W7018750408

Diversity in the Korean Way: Transcultural Identities in Contemporary Diasporic Korean Literature and Media in North America

2022· other· en· W7018750408 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typeother
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismPoliticsNarrativeDiversity (politics)GeopoliticsRepresentation (politics)Korean literatureDiasporaIdentity (music)
DOInot available

Abstract

fetched live from OpenAlex

Literary and visual media representations of diasporic Koreans in Canada and the U.S. have noticeably grown in the twenty-first century, (re)shaping popular culture imaginations of South Korean and Asian subjectivities. From globalized sitcoms such as Kims Convenience to novels, memoirs, and animated cartoons, recent portrayals of Koreans by diasporic Koreans increasingly depict the multifariousness of Korean, Korean Canadian, and Korean American identities through various lenses and vehicles such as local and trans-national/trans-historical perspectives, transnational Korean adoption, and comedy/humour. To capture the significance of what I discuss as the transculturality of diasporic Korean identities, I suggest in this dissertation that new frames of comparison and examination beyond geographical, temporal, and disciplinary borders are required. By demonstrating shared and different geopolitical histories and their effects among diasporic Korean populations in North America in tandem with the diversity and politics of representation within literatures and media produced by diasporic Koreans, I unsettle the knowledge of the Korean Waybeing or becoming Koreanand simplistic nationalist imaginations of hyphenated Asian identities, within histories of Western colonialism and exclusion and marginalization against racial minorities in North America.\nThe first chapter broadly traces: 1) the history of Korean Canadian and Korean American literature and media, 2) the respective political contexts shaping such representations in Canada and the U.S., 3) the development of anti-Asian Racism, racialization, and stereotypes in North America, 4) the modernization and economic rise of (South) Korea since the early-twentieth century. These historical and theoretical frameworks of the first chapter inform the second and third chapters, respectively exploring womens narratives and televisual comedies of diasporic Koreans in North America since the 2010s. Chapter Two comparatively analyzes two novels and a memoir by female diasporic Korean authors, Anne Y.K. Choi, Frances Cha, and Jenny Heijun Wills. In this chapter, I pay careful attention to how Korean-born women negotiate their sense of identity and sexuality within contexts of race relations and racism, racial and gender capitalism, and postcolonial histories of marginalization and oppression in settings in Canada, the U.S., and South Korea. Chapter Three examines different forms of televisual comedies, Kims Convenience, Dr. Ken, and Angry Asian Little Girl, to underscore the influence of humour as an emerging strategy for diasporic representation, and at the same time, how such new vehicles of inclusion are surrounded by conditions of White-centred and commercial logics as well as internalized racism.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.454

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0230.016
Scholarly communication0.0140.007
Open science0.0010.006
Research integrity0.0010.002
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 head0.015
GPT teacher head0.178
Teacher spread0.163 · 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 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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