International Labor Migration and Financial Crisis in Korea
Bibliographic record
Abstract
As the Korean economy became severely depressed due to the eruption of the financial crisis in November 1997, most foreign migrant workers in the country were expected ti return to their home countries. However, only one quarter of them moved out of the country, and recently this number has begun to increase. This study uses government statistics and survey data to explore causes of their relative immobility at both the macro- and micro-level. Main findings from the study are: (1) the amnesty measure, which was a major government policy to reduce the number of illegal sojourners, exerted some positive effect in the first few months after the crisis, but did not in later periods; (2) the migrant workers' return rates are negatively associated with the economic development levels of origin countries, indicating that employment and income opportunities at origins are important factors determining mobility; (3) small- and medium-size manufacturing companies still prefer to hire migrant workers over native workers, due to cheaper wages for the former as well as difficulties in recruiting native workers in 3D jobs; and above all (4) most migrant workers, regardless of their sojourn status, desire to stay in the country since their total earnings are less than their migration costs or not as much as they planned, or since they cannot get a job in their home country. With these findings we can hardly expect a massive return of migrant workers. On the contrary, it may well be suggested that the number of immigrant workers will continue to increase as the country's economy recovers from the depression.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".