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Using Linked-administrative Data to Examine the Impact of Parental Disability on Child Attainment

Using Linked-administrative Data to Examine the Impact of Parental Disability on Child Attainment
使用关联管理数据检查父母残疾对儿童学业成绩的影响
批准号:
2884764
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
翻译
背景人们对残疾父母子女的教育程度知之甚少,这使得他们容易受到教育不平等的影响。其他国家关于父母残疾与子女教育结果之间的关系的现有证据并不一致,而且观察到的联系也因人口、地理和社会经济因素而异。本研究旨在通过使用与英国成长相关的行政数据集来检验父母残疾对子女成就的影响,以填补这一研究空白。行政数据具有规模大、人口覆盖率高、无响应率和流失率低以及跨域的多层次数据的优势,有助于对难以接触到的人口进行分析。同样重要的是,将以往残疾研究中以赤字为导向的重点转移到脆弱性和整个生命过程发展中的适应之间的相互作用上。因此,这项研究还旨在探索这些儿童从童年到青春期后期的教育水平,以及在父母残疾的影响下表现出脆弱性或韧性的亚组。父母的残疾以及个人、家庭和社会特征如何影响孩子的成就?2.在父母残疾的背景下,从童年到青春期后期,儿童成就的发展轨迹是什么?3.在父母残疾的影响下,哪些儿童亚群显示出在教育结果方面的脆弱性或弹性?方法将使用与英国成长(Guie)相关的管理数据集(国家统计局,2022)。Guie Wave-1将2011年人口普查与英格兰的可行性所有教育数据集联系起来,将个人、家庭和家庭信息与教育程度数据联系起来。2011年8月31日年龄在10岁至25岁之间的个人,如果他们在2001-02至2014-15学年在英国接受教育,则包括在贵宾名单中。第二波将涵盖2010-11至2014-15学年的五个脆弱性数据集(即缺勤、排除、英国学校人口普查、需要帮助的儿童和照顾儿童)加入第一波数据集。研究问题将通过先进的量化方法解决。首先,将通过描述性统计分析变量的分布。然后,通过多水平建模,这项研究可以通过考虑潜在的社会、健康和地理不平等的分层,更好地解释父母残疾对儿童结果的影响。为了进一步评估变化,它计划使用数据驱动的方法(例如潜在生长模型),根据数据中不同时间点的变化模式来确定这些儿童的潜在教育亚群/轨迹。监督团队这项研究项目通过ESRC/ADR UK/SGSSS倡议进行,将由爱丁堡大学的Jasmin Wertz博士、爱丁堡大学的Bonnie Auyeung博士和Dundee大学的Louise Marryat博士监督,他们是儿童发展方面的专家,具有先进的定量研究技能。结论据研究人员所知,这是第一项使用Guie相关管理数据来检验父母残疾对英国儿童成就的影响的研究。它可能有助于更深入地了解弱势儿童如何在残疾的潜在代际传播中茁壮成长,并可能对教育和家庭政策及做法产生影响。
英文摘要
BackgroundLittle is known about the educational attainment of children of parents with disabilities, leaving them vulnerable to education inequalities. Existing evidence from other countries on the associations between parental disability and children's educational outcomes is inconsistent, and the observed associations also vary by demographic, geographic, and socioeconomic factors.This study aims to fill this research gap by using the Growing Up in England linked-administrative dataset to examine the impact of parental disability on child attainment. Administrative data have strengths of large scale, high population coverage, low non-response and attrition rates, and multilevel data across domains, facilitating analysis on hard-to-reach populations. It is also important to shift the deficit-oriented focus in previous disability studies to the interplay between vulnerability and adjustment across life-course development. Thus, this study also aims to explore these children's educational attainment from childhood through late adolescence and subgroups that show vulnerability or resilience under the impact of parental disability.Research Questions1. How do parental disability together with personal, household and social characteristics affect child attainment?2. What are the developmental trajectories of child attainment in the context of parental disability from childhood through late adolescence?3. What are the potential subgroups of children that show vulnerability or resilience in educational outcomes under the impact of parental disability?MethodologyThe Growing Up in England (GUiE) linked administrative dataset will be used (Office for National Statistics, 2022). GUiE Wave-1 links 2011 Census to the feasibility All Education Dataset for England, connecting personal, familial, and household information with educational attainment data. Individuals aged between 10 and 25 years on 31 August 2011 are included in the GUiE if they were educated in England from the academic years 2001-02 to 2014-15. Wave-2 joins five vulnerability datasets (i.e. absences, exclusions, English School Census, Children in Need, and Children Look After) covering the academic years 2010-11 to 2014-15 to the Wave-1 dataset. Research questions will be addressed through advanced quantitative methods. First, the distribution of variables will be analysed through descriptive statistics. Then, with multilevel modelling, this study can better account for the impact of parental disability on child outcomes by considering the potential stratification of social, health and geographical inequalities. To further assess change, it plans to use data-driven approaches (e.g. latent growth modelling) to identify potential educational sub-groups/trajectories of these children based on patterns of changes across different time points in the data.Supervisory TeamThis research project through an ESRC/ADR UK/SGSSS initiative will be supervised by Dr Jasmin Wertz (University of Edinburgh), Dr Bonnie Auyeung (University of Edinburgh) and Dr Louise Marryat (University of Dundee), who are experts in child development with advanced quantitative research skills. ConclusionTo the researcher's knowledge, this is the first study to use GUiE linked-administrative data to examine the impact of parental disability on child attainment within the UK. It may contribute to a deeper understanding of how vulnerable children thrive in the potential intergenerational transmission of disability and may draw implications for educational and family policy and practices.
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  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2021
  • 负责人:
    張璐
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: