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Record W3131618309

Heritage language learning and identity construction of 1.5 and second generation Korean Canadians

2020· dissertation· en· W3131618309 on OpenAlexaboutno aff
Hyekyung Song

Bibliographic record

VenueMspace (University of Manitoba) · 2020
Typedissertation
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Heritage languageLinguisticsPsychologyGenealogyHistoryAestheticsArtPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Immigrants’ extensive contributions to Canada include cultural and linguistic diversity, underscoring the need to understand the complexities and identity construction of linguistic minorities. Drawing on sociocultural and poststructural perspectives on language, identity, and power (Duff, 2007, 2019; Foucault, 1978; Norton, 2013), this multiple case study of six university-aged 1.5 and second generation Korean Canadians explores the dynamic interplay of heritage language learning experiences, situated contexts, and identity construction. Drawing on participants’ lived experiences and perspectives, the data include in-depth interviews with the primary participants, a focus group with community leaders, and the researcher’s reflection journals. Offering insight into the participants’ first institutional heritage language learning experiences at a university, the findings reveal how deeply these linguistic minorities’ heritage language learning trajectories and identity construction were situated within complex webs of familial, sociocultural, political and transnational factors, and individuals’ different ways of reacting to the social forces. Endeavors to immerse themselves into a range of linguistic and cultural contexts gave these young adults valuable life lessons and unique identities as Korean Canadians, within which they shifted their bilingual/cultural identities. Their heritage language played a critical role in the participants’ multiple identities, broadening their social spaces. University-aged Korean Canadians’ experiences underscore the importance of sociocultural contexts of linguistic minorities’ identity and heritage language learning, the close relationship between language and identity, and the critical role of institutional inclusion of heritage languages, alongside the role of the home, educational institutions, communities, and society.

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)0.000
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 score0.920
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.014
GPT teacher head0.206
Teacher spread0.192 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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