The digitalization of the European migration policy in the context of the securitization of migration

IF 0.1 Q4 MULTIDISCIPLINARY SCIENCES Tomsk State University Journal Pub Date : 2023-01-01 DOI:10.17223/15617793/480/8
D. V. Alekseev
{"title":"The digitalization of the European migration policy in the context of the securitization of migration","authors":"D. V. Alekseev","doi":"10.17223/15617793/480/8","DOIUrl":null,"url":null,"abstract":"The objective of the article is to analyze the transformation of information systems for controlling migration flows in the EU in cases where migration becomes a security issue, which intensified after the refugee crisis of 2015-2016. Special attention is paid to the use of big data analytics for forecasting migration. The research methods of the investigation were: the problem-chronological method to trace the evolution of the EU regulatory framework in the field of border control digitalization and an interdisciplinary approach to analyze the possibilities of using big data to forecast migration, with sociological and statistical methods to characterize migration flows. The article is based on the legal, statistical and fact sheets documents of the EU and the UN, and the publications of foreign and Russian researchers on this theme. The author considers the main characteristics and functional features of the Schengen information system and its components, identifies the limitations, highlightes the stages of transformation of the system and indicates the achieved and planned results. During the modification of the system, along with expanding the set of alerts, enhanced access is provided for EU agencies, including the possibility of making searches using fingerprints. A key function of the new system is to ensure the cooperation of nation states for prompt, confidential and efficient follow-up of cases, through the data exchange via a secure network. The author infers that the digital transformation of border control is aimed at creating a European-wide information infrastructure to investigate crimes and terrorist acts, generate alerts about the danger of their commission by “suspicious” persons and highlight groups of “unreliable” people whose stay in the EU is undesirable. At the same time, the target risk group is not limited to terrorists and criminals, but also includes illegal immigrants. In addition to border control information systems, big data analytics is used to monitor and forecast migration. Mobile phone call detail records, social media and Google trends become a leveraged data source to study mobility patterns and create profiles of potential migrants in real-time; the provided big data can also reflect emerging trends and support early warning mechanisms of easier monitoring of migration at national, subnational and local levels. Based on the analysis of the documents, statistical and sociological data, the author concludes that European migration policy has been advanced into a kind of risk management, in which, due to the process of digitalization, it is possible to profile groups of migrants and create series of “risk filters” serving to identify, isolate and deflect those whose presence in the EU should be limited.","PeriodicalId":45402,"journal":{"name":"Tomsk State University Journal","volume":null,"pages":null},"PeriodicalIF":0.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tomsk State University Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17223/15617793/480/8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The objective of the article is to analyze the transformation of information systems for controlling migration flows in the EU in cases where migration becomes a security issue, which intensified after the refugee crisis of 2015-2016. Special attention is paid to the use of big data analytics for forecasting migration. The research methods of the investigation were: the problem-chronological method to trace the evolution of the EU regulatory framework in the field of border control digitalization and an interdisciplinary approach to analyze the possibilities of using big data to forecast migration, with sociological and statistical methods to characterize migration flows. The article is based on the legal, statistical and fact sheets documents of the EU and the UN, and the publications of foreign and Russian researchers on this theme. The author considers the main characteristics and functional features of the Schengen information system and its components, identifies the limitations, highlightes the stages of transformation of the system and indicates the achieved and planned results. During the modification of the system, along with expanding the set of alerts, enhanced access is provided for EU agencies, including the possibility of making searches using fingerprints. A key function of the new system is to ensure the cooperation of nation states for prompt, confidential and efficient follow-up of cases, through the data exchange via a secure network. The author infers that the digital transformation of border control is aimed at creating a European-wide information infrastructure to investigate crimes and terrorist acts, generate alerts about the danger of their commission by “suspicious” persons and highlight groups of “unreliable” people whose stay in the EU is undesirable. At the same time, the target risk group is not limited to terrorists and criminals, but also includes illegal immigrants. In addition to border control information systems, big data analytics is used to monitor and forecast migration. Mobile phone call detail records, social media and Google trends become a leveraged data source to study mobility patterns and create profiles of potential migrants in real-time; the provided big data can also reflect emerging trends and support early warning mechanisms of easier monitoring of migration at national, subnational and local levels. Based on the analysis of the documents, statistical and sociological data, the author concludes that European migration policy has been advanced into a kind of risk management, in which, due to the process of digitalization, it is possible to profile groups of migrants and create series of “risk filters” serving to identify, isolate and deflect those whose presence in the EU should be limited.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
移民证券化背景下欧洲移民政策的数字化
本文的目的是分析在移民成为安全问题(2015-2016年难民危机后加剧)的情况下,欧盟控制移民流动的信息系统的转变。特别注意使用大数据分析预测迁移。调查的研究方法是:用问题时间顺序法追踪欧盟监管框架在边境控制数字化领域的演变,用跨学科方法分析利用大数据预测移民的可能性,用社会学和统计学方法描述移民流动。本文基于欧盟和联合国的法律、统计和情况介绍文件,以及外国和俄罗斯研究人员关于这一主题的出版物。作者考虑了申根信息系统及其组成部分的主要特点和功能特点,指出了系统的局限性,强调了系统转型的阶段,并指出了已取得的和计划取得的成果。在系统的修改过程中,随着警报范围的扩大,欧盟机构获得了更大的访问权限,包括使用指纹进行搜索的可能性。新系统的一个关键功能是通过安全的网络交换数据,确保民族国家之间的合作,以便迅速、保密和有效地跟进案件。作者推断,边境管制的数字化转型旨在建立一个全欧洲范围的信息基础设施,以调查犯罪和恐怖主义行为,对“可疑”人员的危险发出警报,并突出那些在欧盟不受欢迎的“不可靠”人员群体。同时,目标风险群体不仅限于恐怖分子和犯罪分子,还包括非法移民。除了边境控制信息系统外,大数据分析还用于监测和预测移民。手机通话详细记录、社交媒体和谷歌趋势成为研究流动模式和实时创建潜在移民概况的杠杆数据源;所提供的大数据还可以反映新出现的趋势,并支持在国家、国家以下和地方各级更容易监测移徙的预警机制。基于对文献、统计和社会学数据的分析,作者得出结论,欧洲移民政策已经被推进到一种风险管理,在这种风险管理中,由于数字化的进程,有可能对移民群体进行分析,并创建一系列“风险过滤器”,以识别、隔离和转移那些应该限制在欧盟存在的人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Tomsk State University Journal
Tomsk State University Journal MULTIDISCIPLINARY SCIENCES-
自引率
0.00%
发文量
0
期刊最新文献
The influence of nonuniform movement of rubble foundation on bearing capacity of brick walls of a historic building Comparison of experimental pile penetration force and calculated by regulatory documents Cross-section geometry optimization of flexural thread using energy criterion Increasing cement strength properties with electrophysical processing of water-cement suspension Temperature effect on flexural bowl determined by falling weight deflectometer testing
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1