Tendencies of High-Skilled Migration coming from Romania. Favourable Legislation and Social Policies
Bibliographic record
Abstract
The external migration of a significant part of Romania's high-skilled population is a social phenomenon which became increasingly frequent starting from the 1990s, right after the fall of the communist regime. The basis for this phenomenon consists of several causes: globalization, the strengthening of international economic relations, and later on, Romania's adhesion to the European Union. Research has shown that of all high-skilled population, the professionals who emigrate more frequently consist of engineers, teachers, medical staff, scientific researchers, economists and architects. Besides, the chosen destinations have been variable throughout time. The first phase in time took place in the 1990s, when a large part of the high-skilled population chose to emigrate for professional purposes in countries such as The United States of America, Canada, Germany or Israel. The second important phase occurred after year 2000, when the focus was placed on EU countries, especially after Romania's integration. Apart from temporary unqualified migration, the number of high-skilled migrants and those who leave the country to continue their studies also soared. The chosen countries generally include Great Britain, Germany, Belgium, France and Austria. Given these differences in the tendencies of high-skilled migration, this paper will offer an insight on how the phenomenon evolved, and the factors that caused these variations in space and time. Most likely, some of the countries that were preferred have been facilitating the integration of high-skilled immigrants in society, as opposed to unqualified ones, through a selective set of laws and social policies which are meant to favour this social category. Therefore, we will discover and analyze various examples and benefits of legislation and social policies which offered social protection to high-skilledimmigrants in various countries. This paper is made and published under the aegis of the Research Institute for Quality of Life, Romanian Academy, as part of the programme co-funded by the European Union within the Operational Sectorial Programme for Human Resources Development, through the Project for Pluri and Interdisciplinarity in doctoral and post-doctoral programmes. Project code: POSDRU/159/1.5/S/141086
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".