The importance of social networks amongst refugees resettled through the Community Sponsorship scheme and The Vulnerable Persons Resettlement Scheme
Bibliographic record
Abstract
The dramatic increase in the number of displaced people in the last decade, predominantly hosted by low and middle-income countries, has prompted a reassessment of solutions to ensure international protection and shared responsibilities for refugees. In response, resettlement programmes have been developed and expanded worldwide, allowing the transfer of refugees from first asylum countries to third countries. In 2014, the UK launched the Vulnerable Persons Resettlement Scheme (VPRS), aiming to resettle 20,000 refugees from the Syrian conflict. Through the programmes, refugees are supported by local authorities and an assigned caseworker to aid their integration processes. Simultaneously, sponsorship programmes, allowing individuals to sponsor refugee families and support their integration processes, have emerged in nearly twenty countries. In Europe, the UK developed the first Community Sponsorship (CS) scheme in 2016. \nBehind the enthusiasm for sponsorship programmes often lies the assumption that sponsored refugees receive better assistance than those resettled by government-led programmes, due to the support provided by volunteers' networks facilitating their integration processes. However, there is a paucity of comparative studies providing evidence supporting this assumption, especially outside Canada, where sponsorship programmes differ significantly from those developed in Europe. Additionally, although the importance of social networks in integration processes is widely recognised, several knowledge gaps exist regarding the formation and development of refugees' social networks and their role in supporting integration processes. \nDrawing on migration literature and social network analysis, this study addresses these knowledge gaps by comparing the social networks of refugees resettled through VPRS and CS with a view to understanding how different types of social connections and resources they provide shape integration processes. In addition to distinguishing between types of relationships and resources, this study's conceptual framework also considers individual-level factors, such as refugees' socio-demographic and migration characteristics, as well as contextual-level factors in shaping social networks and integration outcomes and processes. \nThe findings reveal significant depth and breadth differences between the social networks developed by CS and VPRS refugees, suggesting that through CS, refugees are more likely to develop broader and more diversified social networks compared to VPRS refugees. Differences in the types of resources available through social networks further highlight that sponsored refugees can access more tailored practical and emotional support than VPRS refugees. Utilising the Indicators of Integration framework, the study indicates that these variations in social networks and resources do not always lead to substantial disparities in integration outcomes, particularly in functional aspects, as the presence of a social network is insufficient to overcome structural barriers hindering integration processes. However, the presence of caring relationships providing emotional support among sponsored refugees' social networks underscores the significance of these relationships in integration processes. Specifically, sponsored refugees reported how these relationships enable them to feel more confident and comfortable, develop relationships with the wider community and increase their willingness and ability to reciprocate, positively impacting their integration processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".