Coerced return: formal policies, informal practices and migrants’ navigation
Bibliographic record
Abstract
This article raises two questions: (1) how do formal policies and informal practices intersect in coercing returns of migrants without legal immigration status, refused asylum seekers and those unlikely to get asylum? (2) how do migrants at risk of return navigate the coercion they are exposed to? Focusing on the entanglement of formal and informal practices, we develop a typology of involuntary returns, distinguishing among pushing, imposing, and incentivising policies and practices. This typology invites us to see nuances in the forced and voluntary return dichotomy because coercive practices of implementation are embedded in all these types, but the level of coercion varies in different situations. The paper also investigates how migrants exercise agency by contesting/resisting or complying with the return procedures. The article contributes to the scholarship on returns by unpacking formal and informal policy and practice dynamics and migrant agency. Empirically, the paper is based on observations and documentation of practices derived from field research and 97 interviews conducted with returnees from EU countries and Turkey to Albania, Syria, Iraq, and Afghanistan between 2018 and 2023.
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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 | 0.003 | 0.010 |
| 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 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".