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Parental Social Class and Children's Educational Outcomes: A Longitudinal Analysis of the Millennium Cohort Study and Administrative Data

Parental Social Class and Children's Educational Outcomes: A Longitudinal Analysis of the Millennium Cohort Study and Administrative Data
父母社会阶层与儿童教育成果:千年队列研究和行政数据的纵向分析
批准号:
ES/X012085/1
负责人:
Sarah Stopforth
金额:
$26.52万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --

项目摘要

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中文摘要
翻译
对社会阶级不平等的考察是教育社会学的一个中心研究主题。近几十年来,英国的教育体系发生了一系列根本性的变化。这些变化包括学校的结构和组织、课程、资格和入学年龄的变化。尽管有这些变化,在教育成果方面仍然存在明显的社会阶级不平等。这是一个重要的研究领域,因为在弱势家庭长大的孩子往往没有那么有利的结果,这限制了他们在教育和劳动力市场上的选择和机会。该项目结合了数据的创新和统计方法的进步。该项目将解决一项艰巨的挑战,即制定反映教育成果和广泛的学校一级资格的适当措施。此外,该项目将适当衡量社会阶层和当代家庭中的其他不平等。一个主要的分析目标是在多方面的纵向背景下理解教育中的社会阶级不平等。这将通过应用统计模型来实现。行政教育数据越来越容易获得。大多数行政数据的一个主要限制是没有社会阶层的社会学衡量标准,也很少有儿童背景的衡量标准。社会调查数据的一个局限性是,它缺乏详细的教育成果,特别是在学校早期阶段。为了克服这些限制,我们采取了创新的步骤,分析与千年队列研究(MCS)相关的行政教育数据。MCS通过与同一个人的反复接触,提供了关于儿童、父母、家庭和兄弟姐妹的当代数据的独特来源。MCS是一项大规模研究,从18808名队列成员开始,因此支持全面的统计分析。关联普通中等教育证书(GCSE)数据最近才公布。因此,这个项目是对当代不平等现象的一次非常及时和详细的调查,其规模比迄今为止可能的要大。尽管在实践中许多实证分析并没有充分利用具有时间维度的数据,但社会学家经常使用诸如路径和轨迹之类的广泛隐喻来将青年阶段理论化。拟议工作的一个开创性方面将是从社会学知情的生命历程角度更好地理解复杂的教育不平等。这项工作的一个创新之处在于,它将超越常规统计模型的应用,并应用更复杂的模型来研究教育途径和轨迹。这些模型将利用MCS数据的重复接触特性。该项目将提供有关社会阶级不平等的新的详细实证结果。为了迅速公布研究结果,并迅速从研究界的同行那里获得反馈,研究结果将在国家和国际会议上公布。该项目将为主要国际期刊撰写三篇学术期刊文章。对当代英国教育途径和教育不平等的更全面分析的发展将对这个项目产生深远的影响。研究小组将举办一个特别的影响活动,展示该方法,并与ESRC国家研究方法中心合作开发一个基于网络的培训资源。进一步的创新是,这项工作将变得透明和可重复,有助于逐步改变开放的社会科学。
英文摘要
The examination of social class inequalities is a central research theme within the sociology of education. In recent decades, the British education system has undergone a series of fundamental changes. These include changes in the structure and organisation of schools, the curriculum, qualifications, and the school participation age. Despite these changes, marked social class inequalities in educational outcomes are still observed. This is an important area of study because children growing up in less advantaged families have less favourable outcomes, which limit their choices and chances in education and the labour market. This project combines innovations in data and advances in statistical methods. The project will tackle the difficult challenge of developing suitable measures that reflect educational outcomes and the wide array of school-level qualifications. In addition, the project will appropriately measure social class and other inequalities in contemporary families. A primary analytical aim is to understand social class inequalities in education within a multifaceted longitudinal context. This will be achieved through the application of statistical models. Administrative educational data is increasingly becoming available. A major limitation of most administrative data is that there are no sociological measures of social class and very few measures of children's backgrounds. A limitation of social survey data is that it lacks detailed educational outcomes, particularly in the early school phase. To overcome these limitations, we take the innovative step of analysing administrative educational data that has been linked to the Millennium Cohort Study (MCS). The MCS provides a unique source of contemporary data on the children, parents, households, and siblings, collected via repeated contacts with the same individuals. The MCS is a large scale study, which began with 18,808 cohort members and therefore supports comprehensive statistical analyses. Linked General Certificate of Secondary Education (GCSE) data has very recently been released. This project is therefore a very timely and detailed investigation into contemporary inequalities on a larger scale than has hitherto been possible.Sociologists have routinely theorised the youth phase using broad metaphors such as pathways and trajectories, although in practice many empirical analyses have not fully exploited data with a temporal dimension. A pioneering aspect of the proposed work will be the development of a better understanding of complex educational inequalities from a sociologically informed life course perspective. An innovative aspect of this work is that it will move beyond the application of routine statistical models and apply more sophisticated models to investigate educational pathways and trajectories. These models will capitalise on the repeated contacts nature of the MCS data.The project will provide new detailed empirical results relating to social class inequalities. In order to swiftly promulgate results and to rapidly obtain feedback from peers in the research community, results will be presented at national and international conferences. The project will produce three academic journal articles targeted at leading international journals. The development of more comprehensive analyses of educational pathways and educational inequalities in contemporary Britain will be impactful beyond this project. The research team will host a special impact event showcasing the approach and develop a web-based training resource in collaboration with the ESRC National Centre for Research Methods. A further innovation is that the work will be rendered transparent and reproducible contributing towards a step-change in open social science.
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