Bibliographic record
Abstract
Abstract How do queer refugees experience the city? This question drives this chapter because the lived experiences of sexuality and migration play out in the arena of the city. Queer refugees have recently gained some traction in the literature on migration in general; this chapter argues that the journeys from country of origin to cities of relocation reveal intersectional tensions around material resources. How are refugee displacement journeys governed particularly on the axes of access to shelter, work, and community? Queer refugees escape homo/transphobic contexts to find themselves in situations where they must return to the closet in order to survive. While refugee governance often plays out in the abstract arena of the international—border sites, camps, and detention—the city is positioned here as a crucial space where the political economy of refugee survival plays out. Drawing on extensive fieldwork in Paris, Nairobi, and Cape Town, this chapter examines the netted practices of survival, which involve the state, nonstate actors, and wider civil society. In so doing, the chapter highlights networks of solidarity and various dimensions of violence that queer refugees face even in seemingly progressive urban spaces. The main contribution of this chapter rests on the author’s training as an international political economist who does fieldwork in both the Global North and Global South. Through an international political economy (IPE) approach that centers gender, sexuality, and power in a multiscalar political economy, this chapter aims to highlight how everyday forms of survival illustrate the positioning of queer refugees as misfits within a wider global refugee regime.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".