Discover peer-reviewed journal articles and reports that use ADR UK-funded flagship datasets. This collection is being expanded over time.
Displaying results 21 to 28 out of 28
Breakfast consumption has been consistently associated with health outcomes and cognitive functioning in schoolchildren. Evidence of direct links with educational outcomes remains equivocal. We aimed to examine the link between breakfast consumption in 9-11-year-old children and educational outcomes obtained 6-18 months later.
Dataset used: Education Wales
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In recent years, there has been considerable policy and academic interest in the existence of ethnic inequalities in the Criminal Justice System. A large body of sentencing research has been dedicated to exploring whether ethnic minority defendants are treated more harshly than similarly situated white defendants. This paper extends this research utilizing Ministry of Justice linked criminal justice datasets and multilevel models to assess the effect of ethnicity and other defendant case and contextual factors on sentencing outcomes in the Crown Court. The analysis shows that legal characteristics such as plea, pre-trial detention, offence type and severity are important factors determining sentencing outcomes although they do not fully explain disparities in these outcomes between ethnic groups. Ethnic disparities in imprisonment persist and, in some cases, become more pronounced after controlling for defendant case and court factors. In contrast, ethnic disparities in sentence length are largely explained by legal factors, and after adjusting for other predictors of sentencing outcomes, observed differences between most (but not all) ethnic minority groups and the white British disappear.
Dataset used: Data First: Cross-Justice System - England and Wales
The COVID-19 pandemic meant that, in 2020, students in England were unable to sit their examinations and instead received predicted grades, or “centre assessment grades” (CAGs), from their teachers to allow them to progress. Using the Grading and Admissions Data for England (GRADE) dataset for students from 2018 to 2020, this study treats the use of CAGs as a natural experiment for causally understanding how teacher judgements of academic ability may be biased according to the demographic and socio-economic characteristics of their students. A variety of machine learning models were trained on the 2018–19 data and then used to generate predictions for what the 2020 students were likely to have received had their examinations taken place as usual. The differences between these predictions and the CAGs that students received were calculated and then averaged across students’ different characteristics, revealing what the treatment effects of the use of CAGs were likely to have been for different types of students. No evidence of absolute negative bias against students of any demographic or socio-economic characteristic was found, with all groups of students having received higher CAGs than the grades they were likely to have received had they sat their examinations. Some evidence for relative bias was found, with consistent, but insubstantial differences being observed in the treatment effects of certain groups. However, when higher-order interactions of student characteristics were considered, these differences became more substantial. Intersectional perspectives which emphasise interactions and sub-group differences should be used more widely within quantitative educational equalities research.
Dataset used: Grading and Admissions Data for England
There is limited evidence on the health needs and service access among children and young people who are looked after by the state. The aim of this study was to compare dental treatment needs and access to dental services (as an exemplar of wider health and well-being concerns) among children and young people who are looked after with the general child population.
Dataset used: Looked After Children Dataset - Wales
There is some evidence that exam results are worse when students are acutely exposed to air pollution. Studies investigating the association between air pollution and academic attainment have been constrained by small sample sizes.
Dataset used: Welsh Environment Dataset
In the examination of sentencing disparities, hypotheses related to social class have been relatively overlooked compared to explanations centered on offenders' ethnicity. This oversight is regrettable as both factors often intertwine. In this study, we investigate the mediating and moderating effects between offenders' residential area deprivation and their ethnic background using administrative data encompassing all offences processed through the England and Wales Crown Court. Our findings reveal the following: (i) substantial ethnic disparities among drug offenders, but mostly non-existent across other offence categories; (ii) area deprivation does not explain away the observed ethnic disparities, but pronounced area disparities are found for breach and assault offenses, wherein offenders living in deprived areas are penalized compared to their more affluent counterparts; and (iii) ethnicity and area deprivation interact, but only for breach offenses.
Given the urgency of the transition to net-zero, there is a need for a robust evidence base to support an environmentally sustainable and equitable economy. Employing a linked administrative dataset and using both cross sectional and panel estimation techniques, this study examines employment opportunities and estimates the economic benefits of working in green occupations. Consistent with social role theory, the results indicate that individuals are more likely to work in green occupations if they are white, male, full-time, not represented by a collective agreement, and work for an SME or foreign owned business.
Dataset used: Annual Survey of Hours and Earnings linked to 2011 Census - England and Wales
Children with neurodisability often have complex healthcare and educational needs. Evidence from linked administrative health and education data could improve joint working between services. We aimed to develop a diagnostic code list to identify neurodisability in hospital admission records; to assess the representativeness of this phenotype by characterising children with hospital-recorded neurodisability and their outcomes.
Dataset used: Education and Child Health Insights from Linked Data - England
