Taking Stock of the EU-Turkey Statement in 2024
Bibliographic record
Abstract
Abstract The EU-Turkey Statement of March 2016 aimed to end irregular migration from Turkey to the European Union (EU). Since 2016, the relationship between Turkey and the EU has undergone significant changes. While the EU fulfilled only two of its promises under the Statement, Turkey suspended the implementation of the return component of the Statement in 2020 and stopped readmitting third-country nationals from Greece. Meanwhile, recent judgments delivered by the European Court of Human Rights, such as Akkad v. Turkey and G.B. and others v. Turkey, have shed new light on conditions facing refugees, asylum seekers, and migrants in Turkey. This article aims to analyse the implementation of the EU-Turkey Statement as of 2024 by examining to what extent Turkey and the European Union, as well as its Member States, have fulfilled their pledges and acted in line with the course of action agreed under the Statement. It also aims to investigate to what extent Turkey’s assumed status as a safe third country has changed over the years. Given that the number of irregular passages towards the EU through Turkey has decreased considerably and that the return component of the Statement is not currently implemented, we argue that the assessment of whether Turkey is safe should be made with reference to refugees, asylum seekers, and migrants contained in Turkey as a result of the EU-Turkey Statement arrangements not just those returned under the EU-Turkey Statement.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".