The impacts of disadvantage are intersectionally variable.
While there are separate impacts on a persons’ educational achievement and subsequent career – the combined factors of child poverty, place of residence, ethnicity, and gender on educational achievement and future life chances are complexly intertangled.
The first version of the Sutton Trust’s Opportunity Index was primarily focused on place, deprivation and educational attainment: examining within Westminster constituencies in England the difference in life course between pupils with a history of free school meal eligibility (FSM) and their peers across educational attainment and employment.
It turns out that the impact of disadvantage is modulated by your gender, ethnic background, and where you live.
Intersections intensify
While this was valuable work, it was fairly uncontroversial. The links between poverty, educational opportunity, and career progression are well known, with causal links largely understood.
This update, bringing gender and race into the equation, prompts numerous knotty questions. There is a eugenically deterministic edge to some thinking on the extreme political right, and we are once again increasingly hearing (neurobiologically unfounded) claims that gender and ethnicity are intrinsically linked to intelligence. On the other hand, it is fairly common in mainstream political thought to argue in terms of opportunity: those that identify as female or as Black face different challenges within their career and education that can and do have an impact on life chances. And there is a cultural perspective, around the value that various (place– and ethnically– boundaried) communities place on education and employment, as modulated by gender.
The usual poster-children for this kind of multi-factorial analysis are white working class boys – and the Sutton Trust analysis sees white FSM-marker young people as the key population within the provided data tables.
FSM?
A note here, because we often discuss FSM with only a hazy idea of what it represents: free school meals eligibility is generally linked to benefits eligibility – but can vary council-by-council or even school-by-school. In Gloucestershire, for example, if you are on universal credit and have an annual net earned income of no more than £7,400 a year, or if you are on various other benefits or tax credits, you are eligible to apply for free school meals. But from 2026-27 (as in the rest of the country) you are eligible by default, with the option of an opt-out, if you receive any form of universal credit – with no additional earnings bar.
The FSM indicator, as used by UCAS, OfS, the Sutton Trust, and others is not – in other words – a totally reliable indicator of child poverty. It merely asserts that a student has been assessed eligible for FSM in the last 6 years of their pre-18 education, the metric that unlocks the linked “pupil premium” for the school in question. And it will become less reliable: students who are automatically eligible for FSM will not have the FSM marker in future years, only those who have “targeted FSM” (which will still need to be applied for and unlocks things like holiday activities and food, and school travel assistance) will count.
Some very disadvantaged families who chose not to apply for FSM (or soon, the “targeted FSM” status”) – perhaps for cultural reasons, perhaps out of a lack of knowledge – will not have their children included in this measure. Children of migrants without recourse to public funds will not be shown. Children who attended certain schools, or lived in certain local council areas will not show. FSM, as an indicator of individual disadvantage, is hugely problematic.
Findings: White Working Class
The analysis considers both absolute attainment within particular groups, and the FSM gap (the percentage point gap difference between the average performance of members of a group with the FSM marker and those without), using parliamentary constituencies as a geographic unit (if you spotted the point above about differing FSM rules between local authorities, the constituency boundaries are designed to coincide as much as possible).
The main tables and visualisations focus on White FSM as a sub-group – with the main focus being a modified opportunity index dealing with the life chances of White FSM young people in each constituency (best in Brent, worst in central and west Newcastle). While that broad pattern (best in London, worst in the North East) is familiar from the main ranking, the “London effect” is less stark when we consider White British FSM pupils only.
Here’s a plot of what Sutton Trust have presented – you can choose your region of interest via the filter on the top left, and then highlight a constituency using the search at the top middle. The colours show the White British FSM opportunity ranking, both on the map (mouse over to show all variables) and on the chart below: the latter allows you to plot any two variables against each other.
White FSM pupils represent 49 per cent of all pupils in Knowsley, but just 1 per cent in Ealing, Southall, and Brent West. This is not to say that there is less disadvantage in those areas, it demonstrates that there are less White pupils with FSM markers: many of these constituencies ranked highly in the original index. And two London constituencies (Clapham and Brixton, Hill and Peckham) scored very poorly in the White British FSM index. Every English region features both towards the top and towards the bottom of the table.
What this tells us is that White FSM status itself is not a predictor of poor attainment or poor progression unless we consider place. There are huge variations across England, and it is likely that relatively large areas like constituencies had further variations within them.
I also plotted UCAS entry rates (from 2025) by constituency, allowing you to look at any one of the Sutton Trust variables against them.
The pattern I spotted here was an absence of a pattern. You would think that areas with better attainment would see a higher entry rate – but this isn’t always the case.
Findings: in comparison
There are less FSM marker-holding young people from other ethnicities – and even splitting the White FSM population by gender means that we end up with constituency numbers and proportions too small to analyse. Comparisons between groups, therefore, only happen at the region (ILTS1) level – which, bearing in mind what we know about local effects, means we have to be a little careful about the findings.
I’ve already noted that the London effect is less pronounced for White FSM pupils – this is driven by lower numbers of White pupils and higher numbers of pupils of other ethnicities who live in London. Indeed, just 5 per cent of all White pupils in England live in the capital, compared to more than half of Bangladeshi or Black Caribbean pupils.
If we think about the whole of England, Black Caribbean pupils have the lowest educational attainment, and about 43 per cent of them are eligible for FSM, as compared to 37 per cent of Pakistani pupils and 23 per cent of White British pupils. However White British FSM pupils have exceptionally low attainment: polling suggests that parental experiences and attitudes are among the reasons for this.
Conversely, if you are from a first– or second-generation immigrant background, you have better educational attainment than your longer-settle peers. The report cites Zuccotti and Platt to suggest that a positive familial choice to migrate explains differences in expectations, aspirations, and investments around education. The UK is one of just two countries in Europe to experience this phenomenon.
For all the rhetorical focus on White working class boys, it is White girls with FSM markers who have the lowest education attainment, and the lowest earnings – something that has gotten significantly worse over time. Indian and Asian pupils with an FSM background are more likely to be in the top 20 per cent of earners by the age of 28. But even though as a group Bangladeshi students with an FSM background do 5 per cent better than average, they earn 12 per cent less in employment.
Policy prescription
Nuance is usually discarded fairly quickly when we as a nation discuss the goal of ensuring that place of birth, ethnicity, or gender do not close off educational or career opportunities. But nuance is very much what we get from this work – a complex pattern of cold spots that add a local perspective to a familiar national story around working class Black Caribbean and White British pupils. That young White FSM pupils in the North East have higher attainment and higher progression to universities than in many other areas causes problems with the justification of a geographically focused government mission to drive attainment.
Targeting is not always about regions or broad groupings – it needs to be focused on particular communities in particular areas alongside broader themes (the gender disparity is particularly striking). The Sutton Trust has identified structural and intersectional inequalities – the challenge for the government will be in ignoring the political noise that will come alongside dealing with them.
