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,还没有全面的移徙理论可用于分析移徙过程的复杂性。因此,中档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学,以便在分析上将微观因素与各级政治、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一种中间理论。新制度主义将不同层次的分析联系起来,其理论基础是政治学、社会学和经济学的结合点。它结合了结构-代理维度,同时描述了结构中的个人行为。因此,可以在一个统一的分析框架内审查影响移徙决定的各种复杂因素。从方法上讲,这需要一个分析工具,同时模拟不同层面的因素。因此,贝叶斯网络被用来作为一种创新的工具,以捕捉系统的复杂性,移民决策。在这样做时,移徙决策过程中存在的交叉联系的深度和广度被揭示出来。此外,它还可能为如何影响移徙进程提供新的见解。在区域方面,该提案侧重于哈萨克斯坦。哈萨克斯坦是中亚的经济发动机,呈现出迷人的移徙模式(即移民、迁出、回移和国内移徙),其中部分是出于政治动机。最后,该建议以国内移民流动为中心,在过去三十年中,国际移民研究忽视了国内移民流动,这也是哈萨克斯坦研究不足的领域。通过在移民活跃地区应用新的分析框架和方法,我们正在推进理论,方法和经验层面的基本移民研究。
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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