Report Overview

A major challenge when contextualising admissions to university, or recruitment for jobs, is access to high quality information on a young person’s background, to identify those who should benefit. Granular and verifiable information about prospective students’ socio-economic background is, in practice, limited. As a consequence, universities and employers often need to use ‘proxy’ measures, for example looking at the local area someone grew up in based on their home postcode. But little is known about how well these measures capture individual-level socio-economic status.

This report uses data from the Millennium Cohort Study to look at how various proxies for family background correlate with long-run family income, based on data for over 7,000 children.

Key Findings
  • The number of years a child has been eligible for free school meals is the best available marker for childhood poverty (Pearson correlation = 0.69) and is therefore likely to be the best indicator for use in contextual admissions.
  • FSM eligibility also has fewer biases then other measures, particularly for single parent families and renters who are more often missed by other measures. However, verified data on FSM eligibility is not currently available to universities. • POLAR, an indicator of university participation by local area, is currently a key measure used in contextual admissions in the UK. However, it was not designed to measure socio-economic disadvantage, and is very poorly correlated with low family-income (correlation = 0.22). It is also biased against key demographic groups, including BAME students.
  • TUNDRA, an experimental alternative to POLAR, is also a poor measure of income deprivation (correlation = 0.17), and suffers from similar biases. Both POLAR and TUNDRA are unsuitable for use in contextual admissions.ACORN is the best area-level measure available, as it measures households at a very localised level (around 15 households), is designed to be comparable across the UK, and has a reasonably good relationship to low household income (correlation = 0.56). It is also slightly less biased than other area-based markers. However, as a commercial indicator, it is not free to use, and the methodology behind is it not openly published. • The Index of Multiple Deprivation (IMD) is another good option for an area level marker with a moderate relationship with low household income (correlation = 0.47), and the benefit of being publicly available. However, the measure is biased against those who are BAME, live in a single parent household and who rent. IMD is also not comparable across the four constituent countries that form the UK.
Recommendations

1. To improve targeting to contextual admissions and widening access schemes, universities and employers need further individual data about the socio-economic background of applicants, in particular Free School Meal eligibility. The creation of a “household-income” database, as suggested by the Russell Group, would be beneficial, but is likely to be difficult to implement. As it is already collected in official datasets, we suggest that information on the proportion of time young people have been FSM-eligible throughout their time at school would be a valuable alternative.

2. There should be greater transparency and consistency from universities and employers when communicating how contextual data is used. If they are to take advantage of access measures, it is crucial that applicants are aware of if and how they may benefit from contextualisation. Universities and employers should publicise the criteria, including the measures used, clearly on their websites, along with how and when they are taken into account. The current situation – where different organisations use different indicators in different ways while not being transparent in their use – can lead to confusion.

3. Universities and employers should prioritise use of the most robust measures for contextualised admissions and recruitment. Where free school meals eligibility is not available, priority should be given to ACORN, the best area-level measure, followed by the Index of Multiple Deprivation (IMD). If a basket of measures is used, these most robust measures should be weighted most strongly.

4. The POLAR and TUNDRA measures should not be used in contextual admissions for individual students. While intended as a measure of HE under-representation, rather than socio-economic disadvantage, it can have a counter-productive impact on accurately identifying those suffering from socio-economic and educational disadvantage, and its use by universities in their widening access schemes, or as part of contextual admissions should be avoided.

5. The Office for Students should review the role of POLAR and the inclusion of specific measures of socio-economic disadvantage in advance of the next round of Access and Participation Plans. Despite the stated intentions of the OfS, the current emphasis on POLAR-based targets for widening participation incentivises a narrow focus on this measure by universities. When developing the next round of APP’s, the OfS should consider explicitly including a specific measure of socio-economic disadvantage in targets alongside or instead of POLAR. Free School Meal eligibility, as the basis for the official government definition of disadvantage in schools, would be the natural candidate and would enable a more joined-up national policy approach across schools and HE.