Search vocabulary
A three-stage deductive–inductive process mapped terms from seminal literature, expanded them through highly cited conceptual articles and validated candidate vocabulary against indexed database keywords.
About the review
Mapping conceptual breadth and structural patterns in refugee integration scholarship
This systematic scoping review examines how refugee integration research has developed across disciplines, places, methods, themes, concepts and funding structures.
Purpose
Why this evidence base was created
Refugee integration scholarship is multidisciplinary and conceptually heterogeneous. Integration frequently operates as an umbrella term, while settlement, belonging, citizenship, acculturation, adaptation, social capital, social inclusion and related concepts perform more specialised work.
The review was designed to make this conceptual architecture visible while also examining the research structures that produce it: publication growth, geographic concentration, disciplinary location, methods, target populations, thematic domains and funding reporting.
The Refugee Integration Research Explorer was developed as part of the project Refugee Integration in Scholarship: Conceptual Ambiguity, Geographic Gaps and AI-Assisted Scoping Review. The project team comprises Dr Gabriella D’Avino (University of Birmingham), Professor Jenny Phillimore (University of Birmingham) and Professor Sin Yi Cheung (Cardiff University).
Review workflow
From search development to open research
The workflow combines systematic searching and explicit eligibility procedures with the breadth-mapping purpose of a scoping review.
Search and screening
Revised Boolean searches were applied in Scopus and Web of Science. Records were deduplicated and screened against predefined eligibility criteria for peer-reviewed refugee-integration scholarship published from 2001 to 2025.
Dataset structuring
Bibliographic, open-access, geographic, disciplinary, methodological, population, thematic, conceptual and funding fields were assembled as publication-level metadata.
Structural analysis
The final corpus was mapped across time, study and authorship geography, research design, discipline, population, thematic focus, concepts and reported funding.
Full-text conceptual analysis
A purposive corpus of 200 full texts was examined in NVivo for eight target concepts. Text-search queries located candidate passages and every retained reference was reviewed in context by the researcher.
Validation and open research
A purposively selected 15-article validation subset, comprising 296 passage–concept units, supported comparison of researcher/NVivo and GPT-5.6 classification. The publication-level dataset, codebook and methodological documentation are being prepared for open deposit.
Search development
Validated conceptual vocabulary
Deductive mapping began with thirteen seminal publications and produced a broad candidate vocabulary. Inductive expansion then examined highly cited conceptual articles using manual screening, NVivo word-frequency and text-search queries, and conceptual consolidation. Candidate terms were tested in Scopus and Web of Science keyword fields, producing fifteen concept indicators used in the final dataset.
Integration, settlement, social inclusion, social cohesion, social capital, belonging, adaptation, acculturation, citizenship, assimilation, multiculturalism, incorporation, national identity, ethnic identity and social participation.
Interpretive safeguards
Query-assisted, researcher-reviewed
Text searches supported scale by locating potentially relevant material.
Retrieved passages were read in their sentence, paragraph or page context before retention.
Coded extracts were reduced to the shortest passage that retained the relevant meaning.
Agreement statistics assess consistency between procedures, not the accuracy of either procedure.
Citation and access
Research outputs
The project webpage is available. The stable article link and dataset DOI will be added when those outputs are released.
ArticleForthcoming
Dataset DOIForthcoming
Project webpageView project ↗
Preferred dataset citationForthcoming