The making of ‘skilled’ overseas Koreans: transformation of visa policies for co-ethnic migrants in South Korea
Bibliographic record
Abstract
This paper investigates a transient border between the temporary and (potentially) permanent migration schemes, by reviewing the changes in migration policies relating to Korean-Chinese (Joseonjok) co-ethnic migrants in South Korea in the last 10 years. We pay attention to Working Visit Status and Overseas Korean Status and the fluidity between the two visa streams, to argue that the government utilises the arbitrary notion of ‘skilledness’ as an indicator to distinguish the temporary from the non-temporary migrants. To interrogate how the visa system operates, this paper reviews politics between and within the government, the market and the migrants. Although the government rhetorically uses visa policies as a quality-control mechanism to selectively accept a desirable population, it can only do so by relying on the market to ‘evaluate’ migrants. However, Korean-Chinese migrants are welcomed in the low-skilled employment market to fill labour shortages, and they also contribute to the expanding migration industry as consumers, which stand at odds with the government’s effort to limit ‘unskilled’ migration. The relegation of the state’s responsibility to the market provides an opportunity for migrants to contest the border and negotiate with the state. However, their negotiation comes at the expense of precarisation of their legal status.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".