Do fathers who take a parental leave and stay involved raise smarter children? Evidence from the Millennium Cohort Study (MCS1-MCS6)

休育儿假并继续参与的父亲会养育出更聪明的孩子吗？

• 批准号: 1881428
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1881428
• 关键词: Do; fathers; who; take; parental

According to Lamb (2011, p.23) the major motif of father`s involvement in childcare 'has shifted in turn from moral guidance to breadwinning to sex-role modelling, marital support and finally nurturance'. Shaw and Lohan (2012, p.2) in their policy brief indicate a shift of the concept of fatherhood across cultures towards 'an ideal of a nurturing father'. They also note that fathers are nowadays strongly expected to be involved in children`s lives, and this change is propelled globally by government policies. These policies are, in turn, stimulated by growing evidence on a positive effect of father`s involvement on child`s development. Huerta et al (2013, p.8) found that taking paternity leave positively affects father`s involvement in childcare and house chores. In turn, the results showed an association between fathers` involvement in childcare and better children's cognitive test scores, though this association was of small size. The research is based on datasets from four OECD countries, including three waves from the UK's MCS.Elliot and Norman (2015) attempts to measure paternal involvement in childcare and housework. They state that previous research on father's involvement is lacking quantitative tools to accurately measure it (Elliot and Norman, 2015, p.1). Using cross-sectional data from the 1st sweep of MCS they conceptualize father's involvement and produce two quantitative measures of paternal involvement, 'engagement' and 'responsibility', using CFA. The measurement is based on frequencies of performing child- and housework-related tasks. Produced latent variables are then applied to look into employment and socio-demographic features of involved fathers. The authors assert that measuring paternal involvement is still a matter of wide debate, and call for further research on the topic.Norman et al (2014) investigates predictors of father's involvement. The paper is mainly interested in parents' employment as a predictor of paternal involvement in childcare. Using the MCS, they provide evidence of higher importance of a mother's employment mode than father's working hours to father's involvement. Though focussed on the role of parents' employment, the authors consider a class, race, and household composition, gender of a child, parents' qualifications and age among important predictors shaping father's involvement in childcare.Applying Latent Structural Equation Modelling, the proposed research aims to explore power of father's leave-taking around childbirth as a predicator of his participation in childcare; causal relationships between father's involvement, child's early cognitive outcomes and child's later cognitive outcomes. An advantage of the approach is flexibility of adding paths between covariates (such as father's leave around childbirth, employment and ethnicity) and factors (father's involvement, child early cognitive development) and among factors themselves (direct and mediated effect), which leaves less unanswered questions than multiple GLMs would.An abundant supply of variables in the MCS provides us with a wide choice of indicators for building latent constructs and predictors for running regressions of interest. An amount of waves available gives us freedom to apply longitudinal analysis (as inspired by Steele, 2008, and Wickrama et al, 2016) and be ambitious about time-series analysis.Some authors avoid longitudinal analysis because of its complexity, even when they have the data. Taking advantage of longitudinal data, the project will produce highly original results and interest a wide audience. As better methods of analysis emerge, which allow the latent factors (e.g. indices of development) to be tested for their shapes (distributions) and how they change over time, a wider range of applications will be found for Multilevel Longitudinal Structural Equation Modelling.

根据Lamb（2011，第23页）的说法，父亲参与育儿的主要主题“已经从道德指导转向养家糊口，再到性别角色塑造，婚姻支持，最后是养育”。Shaw和Lohan （2012, p.2）在他们的政策简报中指出，跨文化的父亲概念向“养育父亲的理想”转变。他们还指出，如今父亲被强烈期望参与孩子的生活，这一变化是由政府政策在全球范围内推动的。越来越多的证据表明，父亲的参与对儿童的发展有积极影响，这反过来又刺激了这些政策。Huerta et al （2013, p.8）发现，休陪产假对父亲参与育儿和家务有积极影响。反过来，研究结果显示，父亲参与照顾孩子与孩子的认知测试成绩之间存在关联，尽管这种关联的规模较小。这项研究基于来自四个经合组织国家的数据集，其中包括来自英国MCS的三波数据。Elliot和Norman（2015）试图衡量父亲对育儿和家务的参与。他们指出，之前关于父亲参与的研究缺乏定量工具来准确测量它（Elliot和Norman， 2015, p.1）。利用来自MCS第一次扫描的横断面数据，他们概念化了父亲的参与，并使用CFA产生了父亲参与的两个定量测量，“参与”和“责任”。该测量是基于执行与儿童和家务有关的任务的频率。然后应用产生的潜在变量来研究所涉及的父亲的就业和社会人口特征。作者断言，衡量父亲参与仍然是一个广泛争论的问题，并呼吁对这一主题进行进一步的研究。Norman等人（2014）调查了父亲参与的预测因素。本论文主要关注父母的就业作为父亲参与育儿的预测因子。使用MCS，他们提供了证据，证明母亲的就业模式比父亲的工作时间对父亲的参与更重要。虽然关注的是父母就业的作用，但作者认为，阶级、种族、家庭组成、孩子的性别、父母的资格和年龄是影响父亲参与育儿的重要预测因素。应用潜在结构方程模型，本研究旨在探讨父亲在分娩前后休假作为其参与育儿的预测因素的力量；父亲参与与儿童早期认知结果及后期认知结果的因果关系。该方法的一个优点是可以灵活地添加协变量（如父亲在分娩、就业和种族方面的休假）和因素（父亲的参与、儿童早期认知发展）之间的路径，以及因素本身（直接和中介效应）之间的路径，这比多个glm所留下的未解问题要少。MCS中丰富的变量为我们提供了广泛的指标选择，用于构建潜在结构和预测因子，用于运行感兴趣的回归。大量可用的波浪使我们能够自由地应用纵向分析（受Steele， 2008和Wickrama等人，2016的启发），并对时间序列分析充满雄心。一些作者避免纵向分析，因为它的复杂性，即使他们有数据。利用纵向数据，该项目将产生高度原创的结果，并吸引广泛的受众。随着更好的分析方法的出现，可以测试潜在因素（例如发展指数）的形状（分布）以及它们如何随时间变化，多层次纵向结构方程模型将得到更广泛的应用。