Strategies to Exclude: Temporariness and Return/Readmission Policies of the EU
Bibliographic record
Abstract
Migration governance, migration management and migration crises have been key themes among migration scholars and governments over the last decade. Historically, systemic political economic crises are accompanied by the scapegoating of migrants, often as a strategy to shift the focus away from political and economic decisions taken by states. The EU has been no exception, and political and social tensions around migration are arguably at an all-time high, as European governments aim to protect their interests and manage their borders amidst increasing migration pressures globally. In this paper, we will examine these three EU immigration prevention strategies, with a focus on the recently adopted Pact on Migration and Asylum. Specifically, we ask the following research question: what are the roles of temporariness and return/readmission as important EU strategies to hinder, stop, and exclude the movement of migrants to EU (and Schengen)?
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".