New Institutionalism and Bayesian Networks: Establishing an analytical framework to model migration decision making in rural Kazakhstan
New Institutionalism and Bayesian Networks: Establishing an analytical framework to model migration decision making in rural Kazakhstan
批准号:
265263345
负责人:
Professorin Dr. Gertrud Buchenrieder, Ph.D.
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2015
资助国家:
德国
项目状态:
已结题
起止时间:
2014-12-31 至 2017-12-31
中文摘要
到目前为止,还没有全面的迁移理论可用于分析迁移过程的复杂性。因此,中庸理论应该将各种社会科学的见解整合到一个统一的分析框架中。这一框架需要超越个人,并考虑到移徙的政治经济,以便分析地将微观层面的因素与各个层面的政治、经济和社会因素联系起来。我们建议将新制度主义理论作为研究移民决策的中间理论。新制度主义连接了不同层次的分析,其理论基础是政治学、社会学和经济学的交叉。它在描述结构中的个体行为时结合了结构-代理维度。因此,影响迁移决策的复杂因素网络可以在单一连贯的分析框架内进行检查。在方法上,这需要一种分析工具同时对不同层次的因素进行建模。因此,贝叶斯网络被用作捕获迁移决策的系统复杂性的创新工具。在这样做的过程中,揭示了迁移决策过程中存在的交叉联系的深度和广度。此外,它可能会对如何影响迁移过程提供新的见解。就区域而言,该建议侧重于哈萨克斯坦。哈萨克斯坦是中亚的经济发动机,显示出令人着迷的移徙模式(即移民、移出、返回移徙和国内移徙),其中部分是出于政治动机。最后,本建议以国内移徙运动为中心,在过去三十年中,由于有利于国际移徙研究而被忽视,这也是哈萨克斯坦研究不足的领域。通过在迁移动态区域应用新的分析框架和方法,我们正在理论、方法和经验层面上推进基础迁移研究。
英文摘要
As yet there is no comprehensive migration theory available for the analysis of the complexity of migratory processes. Thus, middle-range theories ought to integrate insights from various social sciences into a unifying analytical framework. This framework needs to go beyond the individual and take into account the political economy of migration in order to analytically connect micro level factors, with political, economic and social factors at various levels. We suggest the theory of New Institutionalism as a middle-range theory for the investigation of migration decision making. New Institutionalism connects different levels of analysis, and the theory is based at the junction of political science, sociology and economics. It incorporates the structure-agency dimension while describing individual behavior in structures. Thus, the complex web of factors influencing migration decisions can be examined within a single coherent analytical framework. Methodologically, this calls for an analytical instrument to model factors at different levels simultaneously. Thus, Bayesian Networks is used as an innovative instrument to capture the systemic complexity of migration decision making. In doing so, the depth and breadth of cross-linkages existing within the migration decision making process are revealed. Moreover, it potentially gives new insights into how migration processes can be influenced. Regionally, the proposal focuses on Kazakhstan. Kazakhstan is the economic motor in central Asia and displays fascinating migration patterns (i.e. immigration, emigration, return-migration and internal migration), which have been partly politically motivated. Finally, this proposal centers on internal migration movements, which have been neglected in favor of international migration research during the last three decades and which are also an under-researched area in Kazakhstan. By applying a new analytical framework and methodology in a migratory-dynamic region we are advancing basic migration research at a theoretical, methodological and empirical level.
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