“We Are Not Foreigners”: Constructing Migrant Subjects through Korean Chinese Migrants’ Claims-Making in South Korea
Bibliographic record
Abstract
In this paper, we approach citizenship as a claims-making process consisting of social construction practices that emerge from ongoing negotiations and contestations. We examine the migrant subject-making process of Korean Chinese migrants in South Korea. We draw on the voices of migrants to discuss how Korean Chinese construct their migrant subjectivity by mobilizing a collective understanding of ethnonational belonging and thereby deploy distinctive strategies to support their claims. Our analysis of the data gathered from ethnographic observations and interviews with Korean Chinese migrant workers, activists, South Korean bureaucrats, and policymakers show that Korean Chinese migrants have called upon blood ties and ethnic affinity, continued allegiance, economic contributions, and human rights to construct themselves as legitimate candidates for citizenship in South Korea. By shifting our analytical focus from the state to the migrant subjectivity that emerges through day-to-day negotiations, we aim to unpack the complicated dynamics of social constructions of citizenship.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".