“How about Asylum Seekers who are Homeless?” The Racialised Logics Behind State Designed Strategies of Containment and Control During Covid-19 and Anti-Racist Alternatives: A Glasgow Case Study
Bibliographic record
Abstract
This paper asks two questions: How has the Covid-19 pandemic been experienced by people seeking asylum who are subjected to United Kingdom (UK) State designed-in destitution? And what might be the alternatives to State produced destitution? To answer these questions, we draw on two case studies from Glasgow, a city unique in the UK for its long history of asylum dispersal and its deeply embedded ecology of third-sector support and asylum advocacy work. We argue that to understand the segregatory power of dispersal and tiered welfare provision as forms of violent migration governance, centring the racialised logics at play is imperative. This provides the framework for developing anti-racist approaches to supporting people made homeless through destitution by design. Using case studies, we explore how the UK Government’s use of ‘emergency hotel accommodation’ for people seeking asylum who are already homeless or are at risk of homelessness, are becoming normalised strategies of containment for racialised others and an extension of the distributed violence of dispersal accommodation that long pre-dates the pandemic. We offer an alternative advocacy-led and rights-based approach to secure refuge for people made homeless by the State.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".