Europe´s Refugee Crisis in 2015 and Security Threats from the Baltic Perspective
Bibliographic record
Abstract
Recent developments in Europe starting with the Russia-Ukraine conflict and ending with the economic and political instability in Greece have given rise to instability in the European Union. Yet, none of the previous crises could be compared with the crisis concerning the current massive influx of refugees into the EU that challenges both solidarity and responsibility of the member states. In this context, it is extremely important to understand the actual security threats related to the refugee crisis, particularly for the Baltic countries that have linked their security with European Union and the NATO. Particularly in Estonia and in Latvia, the refugee crisis has been presented as a high security matter as possible rejection of the EU-migrant could lead to the country’s isolation from the international community, the loss of the NATO security network and its exposure to the security threats from Russia. Alternative decision to accept the refugee quotas could on the other hand create challenges for internal security in terms of legitimacy of national governments and public support to refugee policy. In the light of recent terrorist attacks in France these questions seem even growingly important.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".