Bibliographic record
Abstract
This thesis focuses on the implications of past, and hypothetical future movements of people for the prosperity of natives and residents living in the highly developed regions. The first Chapter discusses the welfare impact of migration in the OECD countries by analyzing recent migration flows (net migration between 2000 and 2010), and total stock of migrants in 2010. The importance of different channels, through which migration affects the wellbeing of stayers, is discussed. In the second Chapter, the theoretical framework from the first Chapter is extended to evaluate migration policies in a multi-country general equilibrium model with endogenous migration and trade. In particular, the economic impact of removing visa and trade barriers between the European Union and five major partners (Australia, Canada, Japan, Turkey and the US) is quantified. Additionally, the proposed model gives theoretical evidence about the relations between migration and trade after imposing exogenous shocks to both types of barriers. The third Chapter proposes an innovative modeling technique to identify the global demographic impact of different migration policies in the EU. The model jointly considers peoples’ endogenous decisions about the country of destination, type of visa to apply for, and the duration of stay. In consequence, the proposed framework provides a micro-foundation for multilateral resistance to migration (a complex structure of dependencies between migration choice options). The research question posed in this paper challenges the capacity of the European Union to attract high-skilled immigrants.
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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 | 0.000 | 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".