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Record W7130655314 · doi:10.5817/cejcs2023-18-7

Hyphenated identities : integration and belonging in Korean-Canadian narratives

2023· article· en· W7130655314 on OpenAlexaboutno aff
Rasha Deirani

Bibliographic record

VenueThe Central European journal of Canadian studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsPrideMulticulturalismIdentity (music)ImmigrationNarrativeVariety (cybernetics)Ethnic groupFocus (optics)

Abstract

fetched live from OpenAlex

Canada prides itself on being a multicultural country, and Canadian culture is described by some as a mosaic composed of distinct parts that take pride in their Canadian-ness. My focus is directed towards Korean Canadians and their hyphenated identities. Korean Canadians, like all immigrants, have faced challenges to integrate into Canadian society, reconstruct their identities and find their own sense of belonging. Ann Y. K. Choi's novel Kay's Lucky Coin Variety (2016), Ins Choi's play Kim's Convenience (2012), and a radio documentary (2018) by Jennifer Yoon all explore themes of identity, integration, belonging and hyphenated identities. In addition to being written by second-generation immigrants, these works share similar histories and discuss the struggles that are still facing Korean immigrants in their attempts to integrate (which presents a current and possibly future challenge to Canada in terms of integration and multiculturalism). Aspects like gender, age, socioeconomic status, and generational perspectives all affect the way these immigrants relate to their surroundings and accept their hyphenated status. By examining these factors and studying the autobiographical elements in these works, I seek to understand the creation of the hyphenated identity and what it means to belong and to be hybrid in a multicultural country.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.582
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.280
Teacher spread0.234 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe Central European journal of Canadian studiesSame topicMigration, Ethnicity, and EconomyFrench-language works237,207