Waiting for what? The feminization of asylum in protracted situations
Bibliographic record
Abstract
Millions of refugees are stuck in camps and cities of the global South without permanent legal status. They wait in limbo, their status unresolved in what the United Nations (UN) calls ‘protracted refugee situations’ (PRS). The material conditions and depictions of such refugees as immobile and passive contributes to a feminization of asylum in such spaces. In contrast, refugees on the move to seek asylum in the global North are perceived as threats and coded as part of a masculinist geopolitical agenda that controls and securitizes their movement. Policies to externalize asylum and keep potential refugees away from the affluent nations of the global North, in which they may seek legal status, represent one strategy of exclusion. This article traces these divergent trajectories of im/mobility and demonstrates how humanitarian space for both groups is narrowing over time. For those seeking asylum in the global North, measures such as increased detention and rapid return to transit countries aim to deter migrants from arriving at all. It is contended that the discrete systems that manage asylum seekers in the global North and refugees in long-term limbo are themselves gendered. European Union policies to ‘externalize’ asylum and keep asylum seekers offshore dovetail with policies by EU member states to ‘build capacity’ for refugee protection in refugee ‘regions of origin’. These represent a shifting, not a sharing, of responsibility for their welfare and prolongs their wait.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.033 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".