The Stranger and the K-Quarantine: Foreigners and Pandemic Response in South Korea
Bibliographic record
Abstract
From the early phases of the pandemic, the South Korean response to COVID-19 has garnered widespread international acclaim. This thesis explores the COVID-19 measures that were implemented in Korea throughout the pandemic in its entirety, that is, from the early successes of 2020, up until the radical lifting of mandates in the spring of 2022. This thesis documents and analyzes the state's COVID-19 containment strategy from the specific vantage point of foreigners living in Korea, a minority group that has been problematized in particular ways during global health crises like COVID-19. I draw upon fieldwork conducted in Seoul from 2021 to 2023, which included semi-structured interviews, participant observation, and informal conversations. Overall, I suggest that the state's technology-mediated virus mitigation strategy contributed to the production of individuated, disciplined subjectivity. In order to situate the COVID-19 response within larger sociocultural and historical landscapes, I begin by examining how previous health regimes sought to manage and control contagion in Korea, before turning my attention to the pre-emptive quarantine that was mandated for all international arrivals. Subjectivity in the context of COVID-19 is also investigated, by comparing my experiences living in Quebec and Seoul during the pandemic. Finally, I analyze COVID-19 public health messaging, focusing on the dissemination of COVID-19 information through emergency text alerts and government websites, as well as printed posters.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".