加快和加强社会经济数据的生成,为被迫流离失所政策和应对措施提供信息

IF 1.8 Q3 PUBLIC ADMINISTRATION Data & policy Pub Date : 2023-12-22 DOI:10.1017/dap.2023.47
Patrick Michael Brock, Harriet Kasidi Mugera
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引用次数: 0

摘要

摘要 据估计,目前全世界有 1.14 亿被迫流离失所者,其中约 88%生活在中低收入国家。各国政府和国际组织要制定有效的政策和应对措施,就需要关于受被迫流离失所影响者(包括收容社区)的可比和可获取的社会经济数据。需要此类数据来了解需求,以及流离失所的复杂驱动因素和持久解决障碍之间的相互作用。然而,此类高质量数据的收集需要时间,而且成本高昂。不断增加的开放数据量和不断发展的创新技术能否加速和加强数据的生成?考虑到被迫流离失所的具体法律和伦理问题,是否有替代数据源、高级统计和机器学习的应用可适用于被迫流离失所的环境?作为世界银行和联合国难民署之间的催化桥梁,被迫流离失所问题联合数据中心召开了一次研讨会来回答这些问题。本文总结了研讨会上提出的新观点,并就被迫流离失所问题社会经济数据实践社区的未来重点领域和前进方向提出了建议。建议今后重点关注的三个领域是:加强和优化住户调查抽样方法;利用其他数据来源估算被迫流离失所社会经济指标;提高数据的可获取性和可发现性。建议方法的三个主要特点是:与现有的 "从数据收集到数据使用 "管道具有很强的互补性;数据责任是内在的,适合被迫流离失所的情况;对业务相关性进行反复评估,以确保持续关注改善受被迫流离失所影响者的成果。
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Accelerating and enhancing the generation of socioeconomic data to inform forced displacement policy and response
Abstract 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.
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审稿时长
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