Practiced and positioned cultural and linguistic identities of a multiracial South Korean family
Bibliographic record
Abstract
This study investigates the linguistic and cultural identities of a multiracial Korean/Canadian family navigating the societal ideologies of Korea, where pure-blood notions heavily influence identity construction. Using Holland et al.'s (1998) theory of figured worlds and Gee's (2011, 2014) framework on identity, this qualitative case study examines how family members practice and are positioned within these ideologies. Data were collected through language portraits (LPs), LP discussions, semi-structured interviews, and journals revealing nuanced dynamics of identity negotiation. The findings highlight the Korean father’s transnational identity, viewing language as a communicative tool rather than tied to national identity; the White Canadian mother’s embrace of a foreigner identity while fostering her children’s Korean identity; and the children’s evolving strategies to assert their Korean identity while resisting outsider positioning. The study highlights the inadequacy of Korean educational frameworks in addressing multicultural realities and calls for curriculum revision to reflect Korea’s diversity while using innovative tools like LPs to foster inclusivity. By bridging personal narratives with societal discourses, this research uniquely captures the intersection of practiced and positioned linguistic and cultural identities, offering critical insights for supporting multiracial families. These findings contribute to broader discussions on multiculturalism, education, and identity in increasingly globalised societies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".