Community Sponsorship in Europe: Taking Stock, Policy Transfer and What the Future Might Hold
Bibliographic record
Abstract
This article explores the recent emergence of community sponsorship of refugees in Europe, an approach which shares responsibility between civil society and the state for the admission and/or integration of refugees. Originally a Canadian model developed to support the resettlement of Indochinese refugees, the model has gained momentum in Europe, with a number of states piloting or establishing community sponsorship schemes. This proliferation, while generally seen as positive for international protection of refugees, has led to conceptual confusion and a significant range of approaches under the “umbrella” concept of community sponsorship. As a result, community sponsorship today may be understood both as a form of resettlement and a complementary pathway to protection. While interest and momentum around community sponsorship is high, little work currently exists mapping and analysing how jurisdictions adopt the community sponsorship model. With reference to existing work on policy transfer, this contribution takes stock of community sponsorship models in Europe; analyses how community sponsorship may become a viable policy option in European states as a form of transnational policy transfer; and sets out a number of challenges for the future development of community sponsorship in Europe.
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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 | 0.023 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.020 | 0.030 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".