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Record W7047828305

The importance of social networks amongst refugees resettled through the Community Sponsorship scheme and The Vulnerable Persons Resettlement Scheme

2024· dissertation· en· W7047828305 on OpenAlexfundaboutno aff

Bibliographic record

VenueUniversity of Birmingham Institutional Research Archive (University of Birmingham) · 2024
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
FundersUnited Nations High Commissioner for RefugeesYork UniversityEuropean CommissionUniversity of Ottawa
KeywordsRefugeeEnthusiasmSocial integrationScheme (mathematics)Social network (sociolinguistics)Social protectionSocial assistanceDisplaced person
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0090.010
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.298
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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