Education and Social Fluidity: A Reweighting Approach

IF 2.7 2区 社会学 Q1 SOCIOLOGY
Kristian Karlson
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引用次数: 0

Abstract

Although sociologists have devoted considerable attention to studying the role of education in intergenerational social class mobility using log-linear models for contingency tables, findings in this literature are not free from rescaling or non-collapsibility bias caused by adjusting for education in these models. Drawing on the methodological literature on inverse probability reweighting, I present a straightforward standardization approach free from this bias. The approach reweighs in an initial step the mobility table cell frequencies to create a pseudo-population in which social class origins and education are independent of each other, after which one can apply any loglinear model to the reweighted mobility table. In contrast to the Karlson-Holm-Breen method, the approach yields coefficients that are comparable across different studies because they are unaffected by education’s predictive power of class destinations. Moreover, the approach is easily applied to models for various types of mobility patterns such as those in the core model of fluidity; it yields a single summary measure of overall mediation; and it can incorporate several mediating variables, allowing researchers to control for additional merit proxies such as cognitive skills or potential confounders such as age. I illustrate the utility of the approach in four empirical examples.
教育和社会流动性:一种重新加权的方法
尽管社会学家已经投入了相当多的注意力来研究教育在代际社会阶级流动中的作用,使用列联表的对数线性模型,但这些文献的研究结果并没有避免由于在这些模型中调整教育而导致的重标度或非可折叠性偏差。根据关于逆概率重加权的方法学文献,我提出了一种没有这种偏见的直接标准化方法。该方法在初始步骤中重新加权流动性表单元频率,以创建一个伪人口,其中社会阶层起源和教育相互独立,之后可以将任何线性模型应用于重新加权的流动性表。与卡尔森-霍尔姆-布林方法相比,该方法产生的系数在不同的研究中具有可比性,因为它们不受教育对班级目的地的预测能力的影响。此外,该方法很容易应用于各种流动模式的模型,例如流动性核心模型中的模型;它产生了一个单一的综合衡量整体调解;它可以结合几个中介变量,允许研究人员控制额外的优点代理,如认知技能或潜在的混杂因素,如年龄。我用四个实证例子来说明这种方法的效用。
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来源期刊
Sociological Science
Sociological Science Social Sciences-Social Sciences (all)
CiteScore
4.90
自引率
2.90%
发文量
13
审稿时长
6 weeks
期刊介绍: Sociological Science is an open-access, online, peer-reviewed, international journal for social scientists committed to advancing a general understanding of social processes. Sociological Science welcomes original research and commentary from all subfields of sociology, and does not privilege any particular theoretical or methodological approach.
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