From international student to international worker? An investigation of international university students’ staying likelihood
Bibliographic record
Abstract
This thesis investigates the factors that are related to international university students’ likelihood of staying in their country of study after graduation. It contributes to the literature on international student mobility, which focuses more on who will study abroad than on investigating its outcomes. Theoretically, the thesis introduces various hypotheses based on several migration theories, including neoclassical theory and migration networks theory, as well as other related literature. Methodologically, it tests these hypotheses using statistical models. The thesis follows the Articles format and consists of three papers. The first paper analyses a secondary dataset that contains information about the stay rate of non-EU students in 25 European countries. It finds that international graduates’ stay rate is higher in destination countries with higher GDP growth rate and lower youth unemployment, and for graduates who come from countries with lower GDP per capita. The stay rate is also higher for graduates whose origin country constitutes a lower share of graduates in their destination country, and for graduates from the United States, Canada and Australia. The second and third paper analyse a large primary dataset collected among international students in the United Kingdom and Czechia. The second paper shows that less affluent students, defined particularly in terms of their parental income, are more likely to stay. A substantial part of this relationship is explained by less affluent students placing greater emphasis on career-related considerations when making their staying decision. The third paper finds that international students’ staying likelihood increased over the course of their studies if they acquired a new partner who is a local or works in the country of study, undertook internships or were involved in student societies in the country of study. It decreased if they were unable to attend lectures due to the COVID-19 pandemic and faced integration difficulties.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".