收集非正常移徙估计和指标信息的工具。

Open research Europe Pub Date : 2025-07-04 eCollection Date: 2025-01-01 DOI:10.12688/openreseurope.20695.1
Carlos Vargas-Silva, Arjen Leerkes, Denis Kierans, Lalaine Siruno, Albert Kraler
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引用次数: 0

摘要

本文讨论了用于收集与测量非正规移民和相关政策(MIrreM)项目的非正规移民存量和流动相关的定量数据的工具。这项工作的最终目标是建立两个数据库,对mirem所涵盖的国家(12个欧盟成员国、联合王国、加拿大、美国和5个过境国)中与非正常移徙有关的估计数和指标进行清查和批判性评价。这些数据库载有对某一国家非正规移徙人口的规模和特征以及这些人口的变化的估计,其中一个数据库集中于非正规移徙人口的数量,另一个集中于流动情况。流动数据库还载有非正常移徙的其他指标清单(例如边境逮捕)。MirreM是秘密项目的后续项目,该项目涵盖2000-2007年期间。MIrreM涵盖2008年至2023年。MIrreM的指导方针根据秘密项目制定的指导方针进行了调整,以保持项目之间的一致性,但也考虑到不同时期和项目总体目的的变化。此外,评估估算值和指标质量的方法也得到了改进,特别是通过明确区分统计指标和估算值,制定不同的评估标准,并收集有关在决策中使用这些数据的信息。除了在MIrreM项目中指导数据收集和分析的直接目的之外,这些工具也可能对其他研究类似主题的研究人员有用,这些主题的特点是缺乏可靠的研究驱动数据,难以达到目标群体,管理数据有限且不完善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Tools for collecting information on irregular migration estimates and indicators.

Tools for collecting information on irregular migration estimates and indicators.

This paper discusses the tools used to collect quantitative data related to irregular migration stocks and flows of the Measuring Irregular Migration and Related Policies (MIrreM) project. The ultimate goal of this exercise was to construct two databases that provide an inventory and a critical appraisal of estimates and indicators related to irregular migration in the countries covered by MIrreM (12 EU member states, the UK, Canada, the USA and five transit countries). The databases contain estimates on the size and characteristics of the irregular migrant population in a given country and the changes in that population, with one database focussing on irregular migrant stocks and the other on flows. The flows database also contains an inventory of other indicators of irregular migration (e.g. border apprehensions). MirreM is a follow-up project to the Clandestino project which covered the period 2000-2007. MIrreM covers the period 2008 to 2023. MIrreM guidelines were adjusted from those developed by the Clandestino project to maintain some consistency across projects, but also to account for changes across the different periods and overall purposes of the projects. In addition, the approach to assessing the quality of estimates and indicators was refined, notably by explicitly distinguishing between statistical indicators, on the one hand, and estimates, on the other, developing different assessment criteria, and collecting information on the use of these data in policymaking. Beyond the immediate purpose of guiding data collection and analysis within the MIrreM project, these tools may also be useful for other researchers working on comparable topics characterised by a lack of robust research-driven data, hard-to-reach target groups and limited and imperfect administrative data.

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