Introduction: Politics of Citizenship and Transnational Gendered Migration in East and Southeast Asia
Bibliographic record
Abstract
Even in this age of globalization when people, ideas and goods readily move across national borders on an unprecedented scale, political rhetoric in support of prevailing notions of the static boundaries of citizenship remain pervasive. In particular, the increasing frequency, intensity and scale of transnational migrations?combined with innovations in transportation and communications technologies?have generated new challenges to the concept of citizenship. In the twenty-first century, it is crucial to understand the transnational and increasingly fluid definitions of collective consciousness and individual identity that cannot be understood in the context of existing conceptions of race and territorially bounded political community. Political communities across nations and historical epochs have included or excluded groups according to different and often shifting criteria. Treating citizenship and a sense of belonging as unfixed and subjected to changes over time, this special issue examines the politics of citizenship in selected East and Southeast Asian countries in the ages of transnational gendered migration. The special issue explores how transnational gendered?including both female and male?migration has affected citizenship or a sense of belonging from interdisciplinary and comparative perspectives. Transnational gendered migration poses a challenge to the notion of citizenship and has been an important instigator of legal and social reforms.2 Japan, South Korea, the
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".