Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response
There are now an estimated 114 million forcibly displaced people worldwide, some 88% of whom are in low- and middle-income countries. For governments and international organizations to design effective policies and responses, they require comparable and accessible socioeconomic data on those affecte...
| Autores principales: | , |
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| Formato: | Artículo |
| Lenguaje: | English |
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Cambridge University Press
2023-01-01
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| Colección: | Data & Policy |
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| Acceso en línea: | https://www.cambridge.org/core/product/identifier/S2632324923000470/type/journal_article |
| _version_ | 1827576310553116672 |
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| author | Patrick Michael Brock Harriet Kasidi Mugera |
| author_facet | Patrick Michael Brock Harriet Kasidi Mugera |
| author_sort | Patrick Michael Brock |
| collection | DOAJ |
| description | There are now an estimated 114 million forcibly displaced people worldwide, some 88% of whom are in low- and middle-income countries. For governments and international organizations to design effective policies and responses, they require comparable and accessible socioeconomic data on those affected by forced displacement, including host communities. Such data is required to understand needs, as well as interactions between complex drivers of displacement and barriers to durable solutions. However, high-quality data of this kind takes time to collect and is costly. Can the ever-increasing volume of open data and evolving innovative techniques accelerate and enhance its generation? Are there applications of alternative data sources, advanced statistics, and machine-learning that could be adapted for forced displacement settings, considering their specific legal and ethical dimensions? As a catalytic bridge between the World Bank and UNHCR, the Joint Data Center on Forced Displacement convened a workshop to answer these questions. This paper summarizes the emergent messages from the workshop and recommendations for future areas of focus and ways forward for the community of practice on socioeconomic data on forced displacement. Three recommended areas of future focus are: enhancing and optimizing household survey sampling approaches; estimating forced displacement socioeconomic indicators from alternative data sources; and amplifying data accessibility and discoverability. Three key features of the recommended approach are: strong complementarity with the existing data-collection-to-use-pipeline; data responsibility built-in and tailored to forced displacement contexts; and iterative assessment of operational relevance to ensure continuous focus on improving outcomes for those affected by forced displacement. |
| first_indexed | 2024-03-08T21:09:23Z |
| format | Article |
| id | doaj.art-58cc8808983349eba184762db143278b |
| institution | Directory Open Access Journal |
| issn | 2632-3249 |
| language | English |
| last_indexed | 2024-03-08T21:09:23Z |
| publishDate | 2023-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Data & Policy |
| spelling | doaj.art-58cc8808983349eba184762db143278b2023-12-22T09:44:55ZengCambridge University PressData & Policy2632-32492023-01-01510.1017/dap.2023.47Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and responsePatrick Michael Brock0https://orcid.org/0000-0002-1035-1619Harriet Kasidi Mugera1World Bank UNHCR Joint Data Center on Forced Displacement, Copenhagen, DenmarkWorld Bank UNHCR Joint Data Center on Forced Displacement, Copenhagen, DenmarkThere are now an estimated 114 million forcibly displaced people worldwide, some 88% of whom are in low- and middle-income countries. For governments and international organizations to design effective policies and responses, they require comparable and accessible socioeconomic data on those affected by forced displacement, including host communities. Such data is required to understand needs, as well as interactions between complex drivers of displacement and barriers to durable solutions. However, high-quality data of this kind takes time to collect and is costly. Can the ever-increasing volume of open data and evolving innovative techniques accelerate and enhance its generation? Are there applications of alternative data sources, advanced statistics, and machine-learning that could be adapted for forced displacement settings, considering their specific legal and ethical dimensions? As a catalytic bridge between the World Bank and UNHCR, the Joint Data Center on Forced Displacement convened a workshop to answer these questions. This paper summarizes the emergent messages from the workshop and recommendations for future areas of focus and ways forward for the community of practice on socioeconomic data on forced displacement. Three recommended areas of future focus are: enhancing and optimizing household survey sampling approaches; estimating forced displacement socioeconomic indicators from alternative data sources; and amplifying data accessibility and discoverability. Three key features of the recommended approach are: strong complementarity with the existing data-collection-to-use-pipeline; data responsibility built-in and tailored to forced displacement contexts; and iterative assessment of operational relevance to ensure continuous focus on improving outcomes for those affected by forced displacement.https://www.cambridge.org/core/product/identifier/S2632324923000470/type/journal_articledata sciencedisplacementinnovationliving conditionssocioeconomic datawellbeing |
| spellingShingle | Patrick Michael Brock Harriet Kasidi Mugera Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response Data & Policy data science displacement innovation living conditions socioeconomic data wellbeing |
| title | Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response |
| title_full | Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response |
| title_fullStr | Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response |
| title_full_unstemmed | Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response |
| title_short | Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response |
| title_sort | accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response |
| topic | data science displacement innovation living conditions socioeconomic data wellbeing |
| url | https://www.cambridge.org/core/product/identifier/S2632324923000470/type/journal_article |
| work_keys_str_mv | AT patrickmichaelbrock acceleratingandenhancingthegenerationofsocioeconomicdatatoinformforceddisplacementpolicyandresponse AT harrietkasidimugera acceleratingandenhancingthegenerationofsocioeconomicdatatoinformforceddisplacementpolicyandresponse |