Recent discussion of POLAR has questioned its utility for targeting underrepresented groups in higher education. But POLAR is, and will continue to be, a powerful tool in the drive for fairer access.
The OfS’s insight event on fairer access and participation in higher education, held earlier this month, saw lively discussion of the POLAR classification – a discussion which has also played out in a number of Wonkhe articles over the past few weeks. POLAR’s critics have argued that using it for contextual admissions risks missing many young people whose circumstances need to be considered.
Yes, used in isolation for this purpose this is a risk. That’s why the OfS is clear that POLAR should always be used in conjunction with other data and information when it comes to decisions about individual students. But POLAR does a number of things that makes it a hugely valuable resource for universities and colleges working hard to close access gaps in their student populations.
How does POLAR fit with the OfS’s objectives?
The OfS promotes equality of opportunity for all students. Our ambition is that future generations have equal opportunities to access and succeed in higher education, and go on to successful and rewarding careers.
It is, perhaps, not widely understood that the Higher Education and Research Act 2017 (which established the OfS) and regulations require us to address under-representation in higher education, not other measures of deprivation and disadvantage.
POLAR – Participation Of Local Areas – was developed to directly identify areas of the UK where young participation rates are low, in effect defining under-represented areas.
POLAR doesn’t attempt to describe why entry to higher education varies across the country (it is likely that different factors are at play in different areas) – it simply identifies the differences. That makes it both a complex synthesis of the various factors that influence access to higher education, and a relatively simple indicator of area-based background. Used to describe sector-level or provider-level differences in access, POLAR shines a light on large and stubbornly persistent gaps in participation.
POLAR measures entry to higher education by age 19 in small geographical areas across the UK. It sorts each area into one of five groups – or quintiles – based on the proportion of young people in the area who enter higher education by the age of 19. Quintile 1 areas have the lowest rate of participation. Quintile 5 areas have the highest rate of participation. Itdoes not assess an area’s socio-economic profile. It is purely and simply concerned with the proportion of young people in a local area who enter higher education.
POLAR as part of the bigger picture
POLAR is only one part – albeit an important part – of the access and participation picture. Access (or the lack of it) to higher education can be related to socio-economic factors and relative levels of poverty. Many other things affect the likelihood of a young person going into higher education – such as gender; ethnicity; whether their parents went to university; the availability of alternative post-18 opportunities.
POLAR’s critics argue that an area-based measure cannot completely capture this complexity and diversity, and is blind to differences between people who live in the same area.
I agree. POLAR groups people together by where they live. We know instinctively that we are not identical in all respects to our neighbours.
But this is also true for other equality dimensions. Focusing on any single measure of equality – the Index of Multiple Deprivation (IMD), ethnicity, gender, or free school meals – will inevitably conceal variations on other dimensions and create blind spots.
POLAR is no exception. But of the range of measures currently available, it has the strongest ability to discriminate between those young people who progress to higher education and those who don’t.
Splitting (data) up isn’t always a bad thing
The Department for Education (DfE) estimates that 26 per cent of English pupils in receipt of free school meals enter higher education by the age of 19. This is the same rate of progression as the POLAR quintile 1 rate. But using POLAR has a wider reach for targeting groups with low participation rates, encompassing over 30,000 more young people than the free school meals measure does.
Not all young people in receipt of free school meals live in POLAR quintile 1 areas (although over 30 per cent of them do). Using POLAR and free school meal measures in combination improves identification of those groups with the lowest participation.
Table 10 of DfE’s experimental statistics shows that entry to higher education by pupil background (free school meals, ethnicity and gender in combination) results in pockets of very low participation. For example, only 13 per cent of English white male pupils in receipt of free school meals go on to higher education.
But within this table are groups large enough to investigate further. Take white males not in receipt of free school meals – 35 per cent of them go on to higher education by age 19 (one of the lowest rates in the table), and they make up over a third of the school year cohort.
OfS analysis of the underlying data shows that white males not in receipt of free school meals who also live in POLAR quintile 1 areas (40,000 pupils) have a participation rate nearly 30 percentage points lower than those who live in quintile 5 areas.
The potential to use more than one measure to uncover groups where differences exist is clear.
Joining the (data) dots for better outcomes
The OfS has set out an ambitious new approach to eliminating access and participation gaps. We are challenging providers to develop stretching targets in their access and participation plans. Our guidance recommends that providers consider targets based on POLAR, but it also allows for flexibility in this choice.
Regardless of the measures used, we want to support providers to make sure that targets are not met at the expense of other equality characteristics.
Our access and participation data dashboard will allow the OfS, providers, students and others to check progress against a wide range of measures.
To support providers further, inspired by UCAS’s Multiple Equality Measure (MEM) we are developing a framework for creating intersectional measures of equality. Our aim is that the framework can be applied to each stage of the student lifecycle, recognising that those groups that are underrepresented on entry to higher education are different from groups that have poorer outcomes at later stages.
Note: This article contains data sourced from the Department for Education’s National Pupil Database. The DfE do not accept responsibility for any inferences or conclusions derived from the NPD data by third parties
This is a weak defence of an unfair approach. We have demonstrated that using POLAR with a good individual measure such as FSM is better than using POLAR alone, but worse than using FSM alone. And the same is true of all other individual measures. If we have good individual measures we can use them in any combination. POLAR adds nothing but confuses with cases not actually disproportionate or disadvantaged. OfS is plain wrong here. We could all agree on simulated data where we ‘knew’ who would truly reduce disproportionality. And then see whether POLAR, POLAR and good measures, or good measures alone created the best result. Willing to try? Publicly?
A big problem with POLAR is that it looks at initial participation in *any* form of HE at any institution. It is, at best, a good proxy for which areas to target if it is decided area-based initiatives are the best way of increasing HE participation.
However, in terms of driving progress on “fair access” to high tariff institutions, there seems little defence in using POLAR data to drive funding and university activity. There is a big problem in terms of underrepresentation of those from many ethnic minorities and those from working-class backgrounds at these high tariff institutions that POLAR is ill-equipped to deal with.
Ethnic minorities are half as likely to live in a POLAR Q1 area as those from white backgrounds due to residential segregation and the fact that there are (literally) only a handful of POLAR Q1 areas in London. POLAR-based targets incentivise universities admissions policies and funding programmes to discriminate against ethnic minorities.
And – given the relatively small numbers of people with the right entry qualifications to enter high tariff institutions – it is often the middle-class students in POLAR Q1 areas who benefit from high-tariff universities being encouraged to focus in these areas, at the expense of working-class students who live in the other 80% of areas. Academic research (e.g. by academics at UWE) has demonstrated that these perverse incentives are acted upon by universities and HEFCE research shows that many HE entrants from POLAR Q1 are socially advantaged on an individual level.
OfS needs to change this KPM as it is not fit-for-purpose as things stand: https://www.officeforstudents.org.uk/about/measures-of-our-success/participation-performance-measures/gap-in-participation-at-higher-tariff-providers-between-the-most-and-least-represented-groups/
If we were sitting here after 15 years of solid progress in widening participation, especially to the most selective universities, then persistence with POLAR would make complete sense. But we’re not – millions have been spent and very little has changed. We all know Einstein’s definition of madness as endless repetition in hope of a different result and yet here we are 15 years later and we still have our own POLAR albatross.
I won’t rehearse the reasons why POLAR is unhelpful in geodemographic terms and why it’s a pretty classic case of an ecological fallacy (https://www.tandfonline.com/doi/abs/10.1080/0309877X.2013.858681). Mainly I’m here to point out that one of its greatest flaws is the inability of HEFCE/OfS to articulate its purpose or utility in a way which can be operationalised by practitioners who don’t have time to delve into its depths, nuances and quirks.
I often commend Herbert Simon’s work on ‘bounded rationality’ to help people to understand why ever more information (another OfS obsession) does not lead to better decision-making for young people. The same holds for access practitioners. The idea of a new ‘dashboard’ and a new measure fills me with the abject dread that can only come from another gimmick that misses the point.
Instead of a charm offensive on WonkHE, the OfS should:
1. Stop the delusion of pretending that there is a neat statistical solution to a complex social field.
2. Ban the use of POLAR targets in A&P plans – they only lead to deadweight and leakage.
3. Work more closely with Ofsted to address schools that have low expectations and/or exclusionary practices.
…as well as all the obvious stuff like contextualised admissions.
Maggie, all in a day’s work an a’ that … but you are flogging a dead POLAR bear. POLAR is discredited and OfS must either accept this and change its preferred metric or change its access Director. Like climate change, it is no longer possible to remain in denial: the rest of the sector now accepts POLAR is not where fair admissions is at.
POLAR does what it says – uses a high resolution geographical frame to put people in groups by their actual HE entry level, not an assumed proxy. It is partially multi-dimensional, because neighbourhoods themselves are. It shows high discrimination, because the UK has strong residential sorting. And it has a small and robust data footprint, making it usable for both targeting and evaluation. It doesn’t seek to partition people with high or low incomes, if it did it would rank by income not HE entry.
I think people have to learn to use it in conjunction with other measures, it can help, it has helped, nobody pretends it is perfect. I’d rather see the sector get on with using the measure effectively rather than spending disproportionate amounts of time trying to find utopia.
Not about “Utopia”. Nor about income, it just does not work We have simulated its use by itself, and in conjunction with other variables, or just those variables without POLAR. POLAR always makes the situation worse in terms of identifying those in need or those most under-represented. Indefensible. Yes it is easy to do but so would doing nothing be. In fact, doing nothing at least would not fake WP and not worsen access by denying help to the majority of disadvantaged students,
“Nobody pretends it is perfect”, but sadly some people still pretend it’s useful beyond a very broad brush that would be just as readily achieved with pre-existing measures…