Bibliographic record
Abstract
【Purpose: This study investigated the Korean nurses' international migration to provide the basic data for establishing plans of supply and demand for nurses and the status of Korean nurses' application for foreign nurse licenses and overseas employment. Method: The subjects were 5.447 nurses who requested English written nurse license to the Ministry of Health and Welfare for the application of foreign nurse license examinations and overseas employment. Human Resources Development of Korea provided documents of nurses migrated to Saudi Arabia. Data were collected from December, 2002 to July, 2003 and analyzed by using descriptive statistics. Result: The total applicants for foreign nurse license were 3,149 for 2 years. In the year 2001, 1.129 nurses applied, 2,020 nurses in the year 2002. Out of 3,149 total subjects, 2,705(85.9%)nurses applied for U. S. A. nurse license. Eighty percent of the applicants of the U. S. A. nurse license examination applied for the New York states. The number of applicants for Canada was 215(6.8%), followed by Australia 88(2.8%), U. K. 86(2.7%), and New Zealand 45(1.4%). Average age of the applicants was 31, 49.0% of them were in their twenties. Three year college graduates accounted for 64.1% B.S.N. 33.9%. Applicants graduated from universities or colleges of Seoul area were 37.3%, followed by Daegu. The total number of nurses employed overseas were 1,291 during 2001 and 2002. Seven hundred thirty eight nurses(57.2%) were employed in the U. S. A.. Average age was 34, 60.9% were 3year college graduates, nurses graduated from Seoul area were 44.9%. No one applied for Saudi Arabian nurse license, 172 nurses were employed during 1999 and 2002, 39.5% of them were in their thirties. Conclusion: The results of this study shows relatively young and experienced nurses have intention to migrate internationally and they actually migrate to other countries. Comparing the number of nurses migrating to other country with the number of newly issued nurse licenses in Korea every year. the percentage of overseas employment was relatively high. To cope with Korean nurses international migration. new policy to monitor the status of nurse's international migration and an institution to deal with the affairs should be established. And the further study is needed to measure nurse's competence and influencing factors of Korean nurses employed in the U. S. A.】
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".