‘Homes for Ukraine’ and the politics of private humanitarian hospitality
Bibliographic record
Abstract
Abstract Within weeks of Russia’s invasion of Ukraine in February 2022, millions of people had fled to neighbouring countries and across Europe. People throughout Europe were mobilised into action, and from the outset, the response to the unfolding humanitarian emergency in Ukraine was a complex and often messy web of private and public initiatives. In this article, we focus on the unique British humanitarian response to the greatest movement of refugees in Europe since the Second World War, known as ‘Homes for Ukraine’ (HfU). We develop our argument in three steps. First, we situate HfU within existing scholarship on ‘everyday humanitarianism’ and private refugee hosting in Europe, locating these within longer histories of private humanitarian action. Secondly, we show how HfU shifts the humanitarian space into the private and domestic sphere, a move reliant on particular conceptions of the ‘home’ as a space of sanctuary and safety. Finally, we unpack the gendered and racialised conceptions of the home and humanitarian hospitality more broadly, and how HfU sits within and outside of the broader bordering practices of the United Kingdom’s refugee response.
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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 | 0.005 | 0.018 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".