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The Administrative Data Research Network is an ESRC-funded project that ran from October 2013 - July 2018. It is currently at the end of its funding cycle and is no longer taking applications. Administrative data research will be taken forward in a new project, to be launched later in 2018.

The kinds of poverty in schools and their impact on student progress

Research overview

There is an understandable desire to offset the impact of disadvantage in initial education, making subsequent educational and life outcomes less patterned by early poverty. This helps policy-makers and practitioners to enhance the value of interventions to reduce the poverty gap (from providing free nursery places through extra funding for schools to contextualised admissions to university). Unfortunately, there is no single existing official measure of disadvantage that can be used either in research or practice that fully encapsulates early disadvantage.

In terms of family income the best single measure is eligibility for free school meals. It has a simple legal and binary definition based on being below a threshold income. It is available for all school students in state-funded settings (via NPD), and is widely used (e.g. for allocating the pupil premium funding). However, there is now evidence that individuals and schools may be inadvertently treated unfairly where they are at or near the threshold for eligibility. Other desirable measures are either not available or are only known from partial survey data (such as parental occupation from LSYPE).

This new project links census data from NPD/SLASC over the early life of each student with what is known about them from LSYPE. This is used to help assess the impact of patterns of poverty on school social segregation and outcomes, using more sensitive measures of disadvantage than have been used in this way before. 


The results of this study will help in understanding the more detailed link between pupil disadvantage, the nature of pupil intakes to schools, and educational outcomes. This is also practically important for a large number of reasons - the school funding formula, use of pupil premium, school inspections and performance evaluation, and identifying effective interventions.  

Government departments  

Data will be used from the Department for Education

Date Approved 

January 2016

Research lead 

Stephen Gorard, Durham University

Page last updated: 24/10/2017