How Important is “Place” in Understanding what drives Inequalities of Opportunity?

The Project Researchers at University College London (CEPEO) have commenced our analysis of our Outreach Metric project cohort in the Safe Researcher Setting, where participant data has been linked by the Department for Education. As we await the results, we have taken an opportunity to look at different ways of understanding the communities we work with, both within the Outreach Metric cohort and across wider HEAT member activity.

In this blog post, we want to explore:

• Different ways to describe our participants and how we might use place-based classifications in our analysis/evidence, not just for our Outreach Metric cohort but our HEAT aggregate and local analysis too.
• Help members to run an export on the system to describe your cohort using the Output Area Classification categories.

How can we describe our participants?

There are many datasets available to us to help categorise our cohort in terms of demographics and higher education (HE) participation. The list is long, including:  IMD, IDACI, POLAR, TUNDRA, SEISA. Recent research has reminded us that there remain persistent pockets of inequality in certain “places”, geographies and localities such as Rural or Coastal or local authorities.

“In England, state school pupils from FSM backgrounds who live in rural villages have on average the lowest chance of going on to higher education, while those living in coastal locations tend to have a lower chance of progressing to higher education compared to their peers living inland.”

Ruskin Institute for Social Equity (RISE), Coast and Country: Access to higher education cold spots in England, (May 2025), p. 3

The research community acknowledges that there are multiple dimensions to understanding inequalities but that socio economic circumstances are a strong determinant:

“the demographic and socioeconomic circumstances of their adolescent households … particularly household income and private renting … explains more of the difference”

Understanding Society, Insights 2026: Barriers to opportunity, (February 2026), p. 38

The Outreach Metric Steering Group is keen for the analysis to include a spotlight on differences between the outcomes living in isolated areas or groups such as coastal or rural. They asked that we explore other classifications that might be more nuanced than our traditional geography-based metrics.

Are we engaging Rural participants in the same way as Urban participants?

The simple answer is yes and no.

Yes, the Outreach Metric cohort has a representative sample of Rural students, but no, because their participation patterns are not quite the same as that of our Urban cohort. 14% of our Outreach Metric participant cohorts are classified as living in a Rural Area compared to 15%  of the 0–18-year-olds nationally. There is some evidence that provision is not the same at Rural Schools when compared with Urban Schools. This may be masked in this data as Rural students may well attend an Urban School.

What can this tell us?

Whilst we are engaging Rural groups of students in outreach, their engagement patterns are slightly different to that of their Urban peers. There may be many reasons for this, including accessibility, travel requirements, local delivery models and the availability of opportunities.

These findings raise important questions for future investigation:

• Does participation in outreach impact outcomes for Rural participants?
• How does this compare to the impact of outreach on Urban participants ?
• How do outcomes for each group compare once other factors, such as prior attainment and socio-economic circumstances, are taken into account?

What is clear is more analysis is needed to understand our work with a recent Outreach Metric cohort. We plan to find out if these patterns persist in more recent outreach delivery by looking at coverage across schools in 2024/25 in collaboration with RISE. We will keep the membership updated on our progress here. We have started to notice changes with more recent engagement of rural cohorts who have not progressed to HE. We plan to explore whether engagement of rural and urban schools has changed over time.

Looking beyond Rural and Urban measures

Rural and Urban classifications provide just one lens through which to investigate outreach participation. To gain a richer understanding of place and community, we will use the Office for National Statistics (ONS) Output Area Classification (OAC) to categorise the cohort with data available in the HEAT Student record (members only).

The OAC clusters neighbourhoods based on a range of household characteristics including:

• Demography and migration
• Ethnicity, identity, language and religion
• Health, disability and unpaid care
• Labour market and housing

All these factors are highly likely to have an effect on HE participation, opportunity and progression.

Which groups are we most engaging in outreach?

There are nineteen groups in the ONS Output Area Classification, but the top ten most populated groups of outreach participants across the total member Outreach Metric cohort are shown in Diagram 1. Analysis of the cohort evidences that outreach is being targeted to the most disadvantaged communities.

However, there are varying outreach engagement patterns with these groups.

For example:

• 52% of participants from Challenged Communities groups engaged before the age of 16, compared with 46% of those from Legacy Industrial and Coastal Communities.
• 16% of Ethnically Diverse Families in Less Connected Communities participated in Summer School activities, compared to just 8% of participants from Legacy Industrial and Coastal Communities.

These differences raise more important questions around how understanding place may help us better understand inequality of opportunity. What factors are at play when delivering different types of outreach activity to different groups of participants? Is this something we need to consider in order to address inequalities, and how do we best co-ordinate this?

Explore Output Area Classification data with your own cohort

The good news is that OAC data is already available within the database for members to access. If you are interested in getting similar breakdowns for your own cohort of participants to understand which communities you are reaching, you can create an export template that will help you export the right fields each time you would like to carry out your own analysis.

Create a Student Export (with OAC data)

1. Select Students for cohort analysis

Navigate to the Students area and apply the following filters (members only):

• :Attached to Outreach Activity = Yes
• :Permission to Track = Yes
• :Has Postcode = Yes
• :Record State = Current

2. Select the ‘Export’ option

In the pop up menu, prepare to export your Student data:

• Give your Export Search a name, for example ‘Participants with Activity and OAC group’
• Select Students with Activities in the ‘Type’ field
• Select ‘Create a new template’

3. Create a new Export Template

In the menu, create a new template so you can use this whenever you want to export OAC group data:

• Give your Export Template a name, for example ‘Participants, Activity, OAC export’

As a minimum, include the following fields in the template:

• Student HEAT ID
• Home Postcode
• OAC Group
• First Outreach Age
• Last Outreach Age
• Activity HEAT ID
• Type

Note: If your organisation has any of the above fields hidden from view on the Student record, they will not appear in the available list of fields to select in the Export Template.

4. Analyse your results

After downloading the export, navigate to File Store on the LIVE database to download the Output Area Classification Groups Table (members only). Open your export file and use this provided table to add the ‘OAC Group Name’ field using a VLOOKUP on the ‘OAC Group’ field.

Once the additional field has been brought into your Student export, you can then create a pivot table to extract the proportion of your students within each OAC Group. The provided table also presents the proportion of national population within each OAC Group.

This data can support you to explore:

• Which OAC groups are most represented in your outreach
• Differences by Activity Type
• Differences between participants engaged at different ages (before age 16/GCSE year, for example)
• How your participant cohort compares with the national population

For example, 8.3% of the population are classified as ‘Rural Amenity’, allowing you to compare the extent to which you are engaging Rural Amenity groups of participants within your own outreach activity.  OAC group data is also provided in the Postcode Profiler (members only).