# Social inequalities and university success.
## Academic performance through the prism of student living conditions

*Inégalités sociales de réussite à l'Université. La performance académique au prisme des conditions de vie étudiante*

*Sociale ongelijkheden in de kans op slagen aan de universiteit. Academische prestaties vanuit het oogpunt van de leefomstandigheden als student*

Joël Girès

Translator: Jane Corrigan

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OpenEdition
Journals

**Electronic version**

URL: https://journals.openedition.org/brussels/7844

DOI: 10.4000/12af0

ISSN: 2031-0293

**Translation(s):**

Sociale ongelijkheden in de kans op slagen aan de universiteit. Academische prestaties vanuit het oogpunt van de leefomstandigheden als student - URL : https://journals.openedition.org/brussels/7826 [nl]

Inégalités sociales de réussite à l'Université. La performance académique au prisme des conditions de vie étudiante - URL : https://journals.openedition.org/brussels/7842 [fr]

**Publisher**

Université libre de Bruxelles - ULB

**Electronic reference**

Joël Girès, "Social inequalities and university success. Academic performance through the prism of student living conditions ", *Brussels Studies* [Online], General collection, no 195, Online since 15 September 2024, connection on 27 November 2025. URL: http://journals.openedition.org/brussels/7844 ; DOI: https://doi.org/10.4000/12af0

This text was automatically generated on November 27, 2025.

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# Social inequalities and university success. Academic performance through the prism of student living conditions

*Inégalités sociales de réussite à l'Université. La performance académique au prisme des conditions de vie étudiante*

*Sociale ongelijkheden in de kans op slagen aan de universiteit. Academische prestaties vanuit het oogpunt van de leefomstandigheden als student*

Joël Girès

Translation : Jane Corrigan

## EDITOR'S NOTE

In order to see the figures in a better resolution, go to the article online and click on "Original" below each one.

<footnote n="1">1 The analysis of social inequalities in relation to educational institutions has a long tradition in sociology; it is practically constitutive of the discipline, whose development and teaching were marked in the French-speaking world by the early works of Pierre Bourdieu and Jean-Claude Passeron on education [Masson, 2005]. These studies established the cultural dimension as a fundamental factor in educational inequality. According to Bourdieu and Passeron, a policy of democratising education is completely inadequate if it is limited to the economic dimension; it must also be accompanied by a pedagogical and cultural transformation of educational institutions, as they place greater value on the knowledge and skills acquired in privileged families, thus playing a part in social reproduction [Bourdieu and Passeron, 1964].</footnote>
2

This perspective has given rise to the development of the notion of cultural capital, which has become so popular that it has practically become synonymous with educational inequalities [Draelants and Ballatore, 2014]. This trend has favoured an inaccurate use of the concept, undoubtedly prompted by the use of the level of education of parents as an indication of the social background of students, naturally becoming a measurement of their cultural capital¹. However, in doing so, we are lumping together various mechanisms whose exact substance remains unclear, under the inequalities identified by the concept. The authors of an analysis of educational inequalities at Belgian universities note that the educational inequalities identified based on the level of education of students' parents may in fact be a measurement of an effect of economic inequalities between them [Vermandele et al., 2012]. Paradoxically, the notion of cultural capital has even reinforced a culturalist vision of educational inequalities, focused on the “cultural deficit” of students from a modest background rather than on the very functioning of educational institutions [Terrail, 2019].

3

This article takes the opposite view to the cultural focus by documenting the fact that purely economic and material dimensions play a role in the production of educational inequalities. This issue is all the more significant when it comes to higher education: in Belgium, a familialist idea of the social citizenship of students prevails, whereby families must bear the cost of higher education [Chevalier, 2018]. The cost is high, as it is not just a matter of paying tuition fees, but potentially of financing a move away from home and all of the related expenses, of which housing is certainly the highest. In fact, families do not always have sufficient means to provide a comfortable life for their children pursuing higher education studies. Of course, these difficulties vary greatly according to the resources available to families: financing years of university studies is much more difficult for the most disadvantaged families. In addition, the conditions for receiving assistance are restrictive, and the scope of such assistance is insufficient to protect students effectively from financial and material hardship. For example, the average annual amount of higher education allowance paid by the Fédération Wallonie-Bruxelles was € 1 215 per year in 2019-2020 [Fédération Wallonie-Bruxelles 2020], which is not enough for students to live on, forcing those in great difficulty to turn to assistance services at universities and the CPAS².

4

Based on quantitative data collected at Université libre de Bruxelles (ULB), my analysis will attempt to show how material difficulties affect the academic performance of students³. The term “performance” has not been chosen randomly, as educational institutions function in part as places where students are judged, ranked or excluded on the basis of their results, thus conditioning their professional and social pathways. The survey took place during the COVID-19 crisis, which was a major socio-economic shock for students. This event had an uneven impact on them, further underlining the economic dimension of inequalities at university, as we shall see. The setting for this survey was the Brussels-Capital Region, which is particularly well-suited to the analysis of social inequalities in higher education: with more than 120 000 students in higher education in 2021-2022 (excluding doctoral students), it is the largest student city in the country [IBSA, 2024]. Furthermore, the Brussels Region is poor and unequal: compared with the other two regions, it has both a higher poverty rate (27,7 % in 2022) and a higher proportion of households with high incomes, indicating greater polarisation [Observatoire de la Santé et du Social de Bruxelles-Capitale, 2020].
# 1. ULB student survey

The data which this analysis is based on come from a questionnaire survey sent by email to all 32 764 students registered at ULB in November 2020 through the ULB administrative services. The questionnaire was sent between November 2020 and January 2021. A total of 4 284 students responded to the survey⁴. It was conducted during the COVID-19 pandemic and the months of lockdown; this situation had an impact on the analyses, which will be addressed later in the article. The questionnaire focused on the living conditions of students: their resources, material and family situations and studying conditions. The data collected were then linked to the administrative data available to ULB in December 2021. They provided detailed information on the academic results of students at the end of the 2020-2021 academic year, i.e. the period targeted by the survey. This information included the average marks obtained for their exams, the number of credits passed or failed, and their degrees. The administrative data also provided details of previous secondary education (stream and school attended) and the degree programme taken at university (level of study, faculty, number of registrations in different programmes). It was therefore possible to explore in great detail the relationship between the socio-economic conditions of students and their academic results.

One of the characteristics which distinguishes universities from other higher education institutions is the presence of a high proportion of foreign students who come to Belgium specifically for higher education. At ULB, for example, nearly one third of students are of foreign nationality, many of whom did not attend secondary school in Belgium [Paume and Cauwe, 2021]. The majority come from European countries – especially France – but there is also a smaller proportion of students from poorer countries, mainly Cameroon, Morocco and Congo. These students have been excluded from the analyses presented in this article because they are in a specific situation: for example, they do not have access to the same rights⁵ and are not present at the same stages of studies⁶, which would require specific investigation. I have therefore only considered students who completed at least their final year of secondary education in Belgium, regardless of their nationality⁷: the sample therefore comprises 3 038 students. The ethno-racial dimension of inequality – which is significant in Brussels – has been analysed: the questionnaire includes questions on the nationality and country of birth of parents, and the experience of racial discrimination during university studies⁸.

# 2. Situations of hardship at university

The aim of this article is to examine the effect of socio-economic conditions on academic performance at university. As a result, I have used a typology of living conditions to classify students. I was inspired by the research perspective on material hardships, which aims to measure poverty based on whether people are able to meet essential needs in order to live decently, rather than on people's income [Boarini and Mira d'Ercole, 2006]. This perspective is especially suited to students, as many simply have no income at all and live wholly or partly with money given to them by their parents. It also has the virtue of being based on the situation experienced by students, rather than making assumptions based on the characteristics of their parents. In order
to measure hardship, eight questions were asked of students, related to the eight items in Table 1. These questions were based on the Survey on Income and Living Conditions (EU-SILC)⁹ questionnaire, and were adapted to student life. The various elements they refer to are considered necessary for a “normal” and decent student life, and not having access to them for financial reasons is therefore considered to be a hardship.

<table><caption>Table 1. Hardships experienced by students</caption><thead><tr><td>Dimension explored</td><td>Element of hardship</td></tr></thead><tbody><tr><td>Social life</td><td>1. Have a drink with friends at least once a month.</td></tr><tr><td rowspan="2">Leisure activities</td><td>2. Participate in leisure activities on a regular basis (cinema, sports, etc.).</td></tr><tr><td>3. Go on a holiday at least once a year.</td></tr><tr><td>Meeting basic needs</td><td>4. Spend a small amount per week on personal needs.</td></tr><tr><td rowspan="2">Availability of materials required for studies</td><td>5. Purchase study resources (textbooks, books, etc.).</td></tr><tr><td>6. Have a computer for academic work.</td></tr><tr><td rowspan="2">Housing conditions</td><td>7. Able to heat home sufficiently.</td></tr><tr><td>8. Have a private bedroom (not shared with another person, other than a spouse or infant).</td></tr></tbody></table>

8

In order to create the typology of hardships, the number of items which students have to do without for financial reasons was counted: when the total is zero, the student experiences no hardship; when it is eight, he or she experiences maximum material hardship. Students experiencing between five and eight hardships were grouped together, as they were few in number. Figure 1 shows the distribution of hardships at ULB: 42 % of students experience no hardships, and 58 % at least one. 5 % of students experience five or more hardships, which can be described as severe hardship¹⁰. The graph shows the number of people in the sample according to level of hardship, so that the reader is aware of the size of the categories used in this article¹¹. The graph also shows the confidence intervals of the estimates in order to provide a measurement of uncertainty (at a 95 % confidence level); these intervals will be displayed wherever possible. Figure 2 shows the types of hardship encountered according to the number of hardships¹². We can see that the hardships encountered most quickly are related to leisure activities, holidays and being able to spend money on oneself, which are the most “dispensable” elements in the sense that they are not vital, unlike being able to heat one's home. We can already understand how material deprivation can affect commitment to and success in academic studies, as 47 % of students who experience severe hardship are unable to heat their homes and 57 % do not have a private bedroom, suggesting a living environment which is unsuitable for studying. Not having a room of one's own – a situation which arises more often when students live with their parents¹³ – has been identified in the literature as an obstacle to completing academic studies successfully [Lynch and O'Riordan, 1998; Harb and El-shaarawi, 2007; Gouvias,
Katsis and Limakopoulou, 2012]. We also note that 80 % of students who experience the most hardship simply cannot afford to buy their course materials.

<figure><img src="image_3.png" /><figcaption>Figure 1. Distribution of the number of hardships experienced by students</figcaption></figure>

Reading: It is estimated that 15 % of students experience two hardships. This concerns 407 students in the sample. The lines at the end of the bar indicate the margin of error: the true proportion is probably between 14 and 16 %.

<figure><img src="image_4.png" /><figcaption>Figure 2. Types of hardship experienced by students</figcaption></figure>

Reading: +/-75 % students who experience three hardships are not able to take one week's holiday per year, enjoy leisure activities or spend a small amount on themselves per week. Another 27 % are not able to buy the textbooks needed for their courses.

9 It is easy to imagine that these hardships have material implications which reduce the ability to carry out one's studies properly. They undoubtedly also have interpersonal
effects on students. Figure 3 shows that the more students experience hardship, the less time they devote to leisure activities, while the time devoted to academic activities (attending classes and studying at home) remains the same. This is not surprising, as we saw earlier that leisure activities are the first to be interrupted in the event of financial difficulties. Correlatively, students who experience hardship are less likely to ask other students for help (figure 4). This observation is in keeping with the results of the qualitative study by Kathleen Lynch and Claire O'Riordan, which shows that students from modest backgrounds are more isolated at university [Lynch and O'Riordan, 1998]. It can be hypothesised that student socialisation is based on leisure activities, and that when students are deprived of these they have fewer opportunities to meet their peers, and therefore to benefit from their help (explanations, sharing course material, etc.), ultimately reducing the chances of academic success.

<figure><img src="image_5.png" /><figcaption>Figure 3. Median weekly time spent on academic and leisure activities</figcaption></figure>

Reading: The median (the value which divides the group in two) of weekly time devoted to academic and leisure activities is 30 hours and 10 hours respectively for students who do not experience hardship. For the students who experience the most hardship, it is also 30 hours for academic activities and only 3 hours for leisure activities.
<figure><img src="image_6.png" /><figcaption>Figure 4. Frequency with which students ask other students for help</figcaption></figure>

Reading: 16 % of students who experience the most hardship never ask for help, compared with 8 % of those who do not experience hardship, i.e. twice as often.

## 3. COVID as a catalyst for inequality

10

As mentioned, the survey took place during the COVID-19 crisis, which has repercussions on the results presented in this article. The economic slowdown caused by the pandemic hit students hard. In particular, bars and restaurants had to close their doors on several occasions during the lockdown periods. The restaurant and café industry (HORECA¹⁴) is a major provider of student jobs [view.brussels, 2020]. In addition, students' parents may have experienced a drop in their income during this period, reducing the possibility for them to help their children financially. The survey shows that over half of students lost income as a result of the COVID crisis, most often due to the loss of their student job or a reduction in the number of hours they worked. Surprisingly, the pandemic even caused the loss of social benefits and assistance for some people, for reasons which are difficult to determine. It also appears that there was not a random social distribution of the effects of the crisis. As illustrated in Figure 5, students who experienced a number of hardships at the time of the survey saw their financial situation deteriorate the most as a result of the pandemic: at the threshold of 3 or more hardships, 8 out of 10 students lost income, compared to 4 out of 10 for those who experienced no hardships. As seen in the graph, the inequality is of the same order if we consider the different sources of income in isolation. The crisis also meant that a small proportion of students returned to live with their parents, perhaps in a living environment less conducive to studying (Figure 6). This return to the family home does not seem to be differentiated socially, even though housing conditions reflect very different realities according to socio-economic level: the survey shows that students with lower social resources are much more likely to have to share their bedroom at home.
<figure><img src="image_7.png" /><figcaption>Figure 5. Financial impact of the COVID crisis on students</figcaption></figure>

Reading: 33 % of students who do not experience hardship lost their student job or had their weekly working hours reduced, compared with 63 % of students who experience the most hardship.

<figure><img src="image_8.png" /><figcaption>Figure 6. The housing situation of students following the COVID crisis</figcaption></figure>

Chi-square of independence: p<0.001

Reading: 36 % of students who do not experience hardship live away from home, compared with 44 % of those who experience the most hardship.

11

It should be borne in mind that the relationship between the number of hardships experienced at the time of the survey and the impact of the COVID crisis may go both ways: a situation of hardship may be partly an effect of the COVID crisis, rather than existing prior to it in its entirety. Hardship is a measurement of the actual situation of students at the time of the survey; the indicator is therefore sensitive to economic changes, not least the pandemic which had begun several months earlier. Nevertheless, the unequal effects of the COVID-19 crisis analysed here are not an artefact of this indicator, as they appear to follow the same logic if we differentiate students according
to the socio-professional category or level of education of their parents: students from
the least affluent and least educated backgrounds suffered more from the COVID crisis.
However, these dimensions show less differences; the typology of hardship thus has the
advantage of facilitating the identification of students whose financial situation is the
least solid in the face of socio-economic shocks, which is a coherent viewpoint if we are
interested in the strictly economic and material dimensions of student living
conditions.

4. Inequalities in terms of marks at university

12

We have seen that students who experience hardship are in a situation which is not conducive to studying, from both a material and an inter-personal point of view. Now let us see if these hardships are indeed associated with poorer academic performance. To observe this, I have made a connection between the hardships endured by students and their academic results based on three indicators: the average mark for the year, the average proportion of credits not validated and the proportion of students who have an average of 0/20.

* Figure 7 shows the distribution of average marks at the end of the year according to the hardships experienced by students¹⁵. The graph represents this distribution in the form of a histogram¹⁶ (grey area) and a boxplot whose limits indicate the different proportions of students around the median. We can see that the greater the hardship, the lower the average for the year. Students experiencing no hardships have a median average of 13,1/20 (half have a higher mark than this, half have a lower mark), while students experiencing five or more hardships have a median of 9,3/20. There is a difference of 3.8 points between these two groups, which is quite considerable.

* Figure 8 shows the average proportion of non-validated credits according to hardship group. As the number of hardships increases, so does the number of non-validated credits: the average proportion of failed credits is almost twice as high among those who experience the most hardships compared to those who do not (40 % vs. 21 %).

* Figure 9 shows the proportion of students with a 0/20 average. This is an indicator designed to measure withdrawal from studies: I consider that an average of 0/20 for the year represents a withdrawal from studies. The third indicator reveals a significant threshold effect at five or more hardships, with students in this situation dropping out three to four times more often than others.
<figure><img src="image_9.png" /><figcaption>Figure 7. Distribution of average marks for the year</figcaption></figure>

Reading: The median average for the year for students who do not experience hardship is 13,1/20. 50 % of them have an average mark between 9,7 and 15. On the other hand, the median is 9,3/20 for the students who experience the most hardship. 50 % of them have an average mark between 5,4 and 12,5, which is much worse.

<figure><img src="image_10.png" /><figcaption>Figure 8. Average proportion of non-validated credits</figcaption></figure>

Reading: Students who do not experience hardship failed an average of 21 % of their credits, compared with 40 % for students who experience the most hardship.
<figure><img src="image_11.png" /><figcaption>Figure 9. Proportion of students with an average of 0/20</figcaption></figure>

Reading: 2 % of students who do not experience hardship have an average of 0/20, compared with 9 % of students who experience the most hardship.

13 Two lessons can be drawn from these initial analyses. The first is that there is a relatively continuous social gradient when it comes to academic performance: students experiencing the most hardships have by far the worst average, but there is already a difference of more than a point between those experiencing no hardships and those experiencing only one (Figure 7). The same is true for failed credits: students who experience two hardships fail almost twice as many credits as those who experience no hardships (Figure 8). This result reveals that academic inequalities between students are indeed associated with inequalities in living conditions; we shall see in the rest of the article the extent to which they may be the cause. The second lesson to be drawn is the particularly difficult position of students who experience the most hardships. The indicator of the proportion of students with a 0/20 average (Figure 9) underlines the potentially decisive role of material difficulties in academic success, as it suggests the existence of a threshold of material difficulties above which it becomes very difficult to pursue studies successfully, leading to withdrawal from studies. There is also a more marked drop in performance for the category of students with the greatest difficulties, if we look at average marks and the proportion of validated credits. Overall, we can see that the students with the most difficulties are in a very poor academic situation: more than half have an average below 10/20 and almost one in ten withdraw from their studies. Students who experience severe hardship represent 5 % of the university population, i.e. more than a thousand individuals, which is not marginal.

14 Given the timeframe of the survey, we wonder what impact the COVID-19 crisis has had on these results. The literature in the sociology of education is sufficiently extensive to rule out the idea that academic inequalities are specific to this period: it has been widely objectivised that family resources condition success at university [Vermandele et al., 2012; Lafontaine et al., 2012]. However, the pandemic may have redrawn the outlines of these inequalities. As we have seen, it may have increased the withdrawal rate of the most precarious, who faced more difficulties during the crisis; or, on the contrary, the greater leniency of professors during that period may have narrowed the gaps [Hutin, 2021]. It is not possible to know for the moment, but answers may be provided later, as the second part of this survey is currently being carried out; it will show whether or not the trends described in this article are continuing.
## 5. Hardship as a tool for analysing social relationships

15

Of course, correlation is not causation. The fact that students who experience great hardship tend to do less well is perhaps the effect of another underlying social logic. Despite its apparent simplicity, the cumulative hardship indicator is a good indicator of major social relationships. The following four figures illustrate this: they break down students experiencing greater or lesser hardship according to their parents' socio-professional status, level of education and country of birth, as well as their age. The socio-professional category of parents¹⁷ is a good indication of the level of household income. Figure 10 shows that students who do not experience hardship are around four times more likely to have parents who are senior executives and four times less likely to have parents who are unemployed than students who experience the greatest hardship, leaving little doubt that the former generally have access to greater financial resources. The level of education of parents is a classic indicator of a student's cultural capital. Figure 11 shows the highest level of education of both parents, and reveals that students who experience the least hardships have parents with a higher level of education who are therefore probably more familiar with academic subjects. Figure 12 shows the country of birth of the first parent mentioned in the questionnaire¹⁸; it unequivocally shows that the hardship experienced by students has an ethno-racial dimension, as the students with the greatest difficulties have a parent born outside Europe in 55% of cases, compared with 10% for students who do not experience hardship. Finally, Figure 13 shows that the students with the most difficulties are older for the same level of education (not shown), no doubt revealing a more chaotic educational pathway (more frequent repetition of years at secondary and higher education level), but also possibly a late return to studies.

<figure><img src="image_12.png" /><figcaption>Figure 10. Socio-economic category of parents</figcaption></figure>

Reading: 37 % of students who do not experience hardship have a parent who is a senior manager, and 12 % have a parent who is unemployed. These proportions are 8 % and 47 % respectively for students who experience the most hardship.
<figure><img src="image_13.png" /><figcaption>Figure 11. Level of education of both parents</figcaption></figure>

Reading: 47 % of students who do not experience hardship have a parent with a university degree, compared with 22 % of students who experience the most hardship.

<figure><img src="image_14.png" /><figcaption>Figure 12. Parents' country of birth</figcaption></figure>

Reading: 71 % of students who do not experience hardship have a parent born in Belgium, compared with 38 % of students who experience the most hardship.
<figure><img src="image_15.png" /><figcaption>Figure 13. Age of students</figcaption></figure>

Reading: 18 % of students who experience the most hardship are aged between 26 and 35, compared with 6 % of students who do not experience hardship; the former are therefore older.

## 6. The determining role of material hardships

16

It is certainly all of the above-mentioned elements which determine student success, and not just financial resources. In order to understand what is at work in this configuration, let us look at the results of a multiple linear regression with the average mark for the year as the dependent variable, and a set of variables which allow us to take into account the effects of the various social relationships mentioned. In order to do this, the variables presented earlier in the descriptive analyses are used according to the same construction, at times simplified¹⁹. Variables linked to the previous educational pathway are also introduced, such as stream and whether or not the student repeated a year in secondary school, as educational pathways and events along the way are themselves identified as having an effect on what happens next [Lafontaine et al., 2012]. The aim is to establish whether an increase in material hardship is still associated with a lower average mark when controlling for other effects. From a technical point of view, this regression is carried out by introducing only qualitative variables as predictors, transformed into dichotomous variables for each of their modalities. This solution has the advantage of allowing the coefficients of each variable to be interpreted directly as deviations from the average mark in relation to the reference category, while keeping the other variables constant. The adjusted R² of the model is 0,255, which shows that a certain amount of variability is not captured by the model, revealing that academic performance is certainly not just a mechanistic translation of major social variables. Nevertheless, the model shows significant deviations from the mean, which we shall now examine (Figure 14).
<figure><img src="image_16.png" /><figcaption>Figure 14. Regression on average marks for the year</figcaption></figure>

Reading: This graph shows the results of the regression modelling the average marks. Students whose parents were born in Europe (outside Belgium) have on average 0,5 points more for their average mark for the year than students whose parents were born in Belgium, controlling for other variables, i.e. the same level of study, age, gender, etc.

17 It appears that most of the dimensions introduced into the model have an effect on students' marks, suggesting that none of them can be explained by one of the others. First-year students have - by far - a lower average for the same social characteristics and age (four and a half points lower average than master's students). There are two possible explanations. The first has to do with the profile of the students: the less academic students, who are more likely to fail, may be over-represented in the first year of their bachelor's degree, and do not manage to get past this first level. The second has to do with university logic: bachelor's courses are less supervised and assessments are probably less lenient and are based on the memorisation of large corpora. Unsurprisingly, women have an average which is almost one point higher than men. Many analyses have documented that women do better than men at university for the same social level [Lafontaine et al., 2012; Alaluf et al., 2003].

18 The regression shows a gap of just under one point between the most and least educated families, with equal parental occupation and student hardship. This effect has been documented extensively in the literature, and it holds true here: from early childhood, the children of highly educated parents acquire tastes, aptitudes and knowledge which will be more “profitable” on the education market, thus representing (cultural) capital [Vermandele et al., 2012]; these parents also have higher educational aspirations for their children [Maroy and Van Campenhoudt, 2010]. In addition, the model shows that the level of education of parents continues to have an effect during university studies, even when the educational background is taken into account (type of stream or repeating a year in secondary school). However, students who devote more
time to academic activities (attending classes and studying at home) are more successful than others, even with the same parental level of education, underlining the fact that success is not only determined by major macro-social variables, but is also based on individual logic.

19 An important point to emphasise is the effect of the parents' country of birth, even when social characteristics are equal. Students whose parents were born in a European country outside Belgium have a slightly higher average than students whose parents were born in Belgium, and the opposite is true for students whose parents were born in the Maghreb or in a sub-Saharan African country, whose average is more than one point lower. This finding is important because this dimension is not often objectified due to a lack of data; it potentially reveals the structuring of academic pathways based on racialisation. It is possible that, for these students, the effect of the country of birth of their parents is linked to other characteristics which are not controlled for. But we can also hypothesise that there are cumulative class and ethno-racial disadvantages for these populations, the latter not being solvable by the former. Several mechanisms may explain this ethno-racial disadvantage: they may be rooted in the family resources of these students, with their parents potentially working in jobs which are less valued than those which they are qualified for as a result of racial discrimination [Pfefferkorn, 2011]; they may also lie in the workings of the university institution, as teaching staff may evaluate students unfairly on the basis of racial prejudice [Rovai, Gallien and Wighting, 2005]. The data show that 16% of students with a parent born in a sub-Saharan African or Maghreb country say they have experienced humiliation of a racist nature at ULB²⁰, from other students and/or staff.

20 But the central fact in my argument is that even after controlling for all of these dimensions, material hardship is still associated with a lower average mark. The effect is visible as soon as there are one or two hardships, although it is slight; however, it becomes very pronounced when at least five hardships are experienced, with the model estimating a decrease by more than two points compared to a situation without any hardships. This situation more often concerns students from modest backgrounds (see above), but the model tells us something else here: the effect of hardships on marks is independent of the social and family background of students. Even students from families with no real financial problems can experience hardship (see above), potentially due to the high costs involved in moving out of the family home, or a lack of family support. Without collective protective measures, the transition from childhood to adulthood is a time of greater vulnerability for many students. Let us not forget that even at a Belgian university such as ULB, where students are known to be from a rather privileged background [Vermandele et al., 2012], more than one out of two students is confronted with at least one hardship. The descriptive analysis of hardships at the beginning of this article shows the mechanisms by which hardships can have a negative impact on academic performance: housing which is too small or noisy, lacking privacy and comfort, thus making it unfavourable to studying; difficulties in buying course materials, making it impossible to keep up with the subject matter; lack of a social life, complicating student sociability and peer support. This result reinforces the idea that material constraints are indeed an obstacle "in their own right" to the successful completion of higher education. When reading this analysis, one must bear in mind that the survey took place during the COVID-19 pandemic, which may have added to the material difficulties of those who were already experiencing them. The crisis may therefore have increased the disparities described in this article, but it also serves as a
reminder that material difficulties can still be an obstacle for students. The continued
existence of this obstacle outside the period of crisis will be documented in the next
part of this survey.

Conclusion

21

The aim of the analysis presented in this article was to document the reality of inequalities in university education in general, focusing in particular on the situation at Université libre de Bruxelles. Three points stand out. The first is that there are marked academic inequalities between students according to their financial resources. Universities thus contribute to transforming social inequalities into academic inequalities.

22

The second important element is that there appear to be many social inequalities, which stem from different social relationships: racialisation or class, for example. I think it is important to underline the existence of ethno-racial inequalities at equal social levels, which are often poorly documented for lack of data and are thus reduced to the socio-economic dimension. This question is all the more significant in Brussels, where a large proportion of young people are the descendants of Turkish and Moroccan immigration in the 1960s, which took place in order to make up for the lack of manual labour, and where social inequalities are therefore superimposed on ethno-racial inequalities [Mazzocchetti, 2012; Jacobs and Rea, 2007].

23

The third noteworthy element, which is at the heart of this article, is the fact that the greater or lesser economic difficulties experienced by students seem to be a factor in the creation of academic inequalities. This may seem to be a trivial assertion, but it is not taken seriously enough when dealing with social inequalities in education. For example, university success measures (guidance, coaching, etc.) are partly based on the idea that the problems faced by low-income students stem from some form of “cultural deficit”. These measures are nevertheless important, but there are undoubtedly students who face material difficulties and therefore conditions which are not conducive to studying, and even less so in times of crisis. Besides these measures, social assistance for students remains very limited. On the one hand, the proportion of students who receive assistance is low in Belgium. On the other hand, the amount of this assistance is often insufficient to live decently.

24

There are two complementary and non-exclusive possible solutions to this situation: the first is, of course, to reduce social inequalities in living conditions and housing between the families of these students, as we have seen that the inequalities they experience at university are at least partly the result of these. The second is to provide decent living conditions for low-income students who are currently studying. It is clear that current assistance measures are not satisfactory from this point of view, for the reasons mentioned in the previous paragraph, and because they operate on the basis of assistance, making it difficult and potentially stigmatising for students to prove their need. Furthermore, the fact that students turn to the CPAS more and more for benefits means that it is deviating from its primary function of providing residual assistance, acting as a last safety net for individuals. On the contrary, the fight against academic inequality could be achieved through much more extensive and less conditional structural aid. The egalitarian effect of this system would be immediate, by providing decent living conditions for students who are currently facing material difficulties.
Furthermore, it would ultimately open up access to higher education, sending a message of true financial accessibility to those who are still excluded.

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## NOTES

1. The reason is that the level of education of parents is a variable which is easier to collect and use than their income or socio-professional position.

2. CPAS, or Centres publics d'action sociale, are municipal bodies which – under certain conditions – guarantee social assistance to people excluded from social security benefits, such as unemployment benefits. This is the case for students.

3. This survey was carried out on the initiative of the Observatoire de la vie étudiante at ULB. I would like to thank Juliette Paume and Jade Cauwe, who helped develop a system for carrying out this survey.

4. The resemblance of the sample to the study population was checked for known socio-demographic variables in the population (level of education, age, gender, nationality). As the focus of this analysis is on academic performance, a comparison of indices referring to this dimension was also carried out. The comparison shows that the sample is distributed fairly similarly to the population for all of these variables, revealing a diversity similar to that of the population. For example, the quartile values for the average marks are 8,36, 12,03 and 14,33 out of 20 in the sample, compared with 7,7, 12,12 and 14,54 out of 20 in the population. It is therefore not unreasonable to assume that overall, the sample is “representative” of the population. However, there is an under-representation of students with the lowest marks. The survey allowed us to gather information on these students, as the sample includes just over 5% of students whose average was less than 1/20 at the end of the year (compared with 9% in the general population), no doubt thanks to the fact that the survey was carried out at the beginning of the academic year (before the first exam session and potential withdrawals from studies). In order to minimise bias, I nevertheless mainly carry out analyses with a view to comparing social groups, as this type of analysis is less affected by the over- or under-representation of one group or another, with the impact of their relative sizes being neutralised by the fact that they are differentiated in the analysis. As a result, even if some groups responded more than others in the sample, the relative differences between the groups are still indicative of the social mechanisms at work in the study population. I therefore consider the data collected as a sample allowing statistical inferences to be made.

5. Grants are not available to them unless they have been in the country for 5 years, and for people with student visas, applying for CPAS assistance is likely to result in the loss of residency rights.

6. Foreign students from sub-Saharan Africa, the Maghreb and Asia are practically only registered at master's level.

7. This does not mean that the study conditions of foreign students are not important. 26% of students from poor countries, mainly from sub-Saharan Africa and the Maghreb, say they cannot afford to heat their homes (vs. 5% of students who attended secondary school in Belgium), and 49% cannot afford to buy their study materials (vs. 14%). As a result, these students are by far those in the greatest material difficulty. The issue simply cannot be addressed in this article.

8. In this article, when I speak of ethno-racial inequalities, I am referring to the social relations of power and domination which assign inferior positions and resources to social groups (called “ethnic minorities”), due to their skin colour, nationality, religion, language, etc. I therefore consider ethno-racial groups as social constructs which come into existence as a result of these relations of power. For more details on this perspective, see [Safi, 2013].
9. See the explanatory pages of the survey on the Eurostat website: https://ec.europa.eu/eurostat/fr/web/microdata/european-union-statistics-on-income-and-living-conditions.

10. This distribution should be interpreted with caution: it is a univariate statistic, and therefore highly dependent on the potential presence of selection bias. However, the result is significant enough to be shown: if there is a bias, it is likely to be related to an over-representation of students experiencing the least hardships. Even so, the proportion of students experiencing at least one hardship is already high.

11. The number of students in the categories of hardship varies slightly between the different analyses in this article, due to some missing responses for the different variables. Observations with at least one missing value for one of the variables were in principle not deleted, in order to avoid reducing the sample size unnecessarily for each analysis. Group sizes were checked systematically; they are no longer indicated here for the sake of clarity.

12. Most of the results and graphs presented in this article were produced with fonctionr, a package for R which I developed with the help of François Ghesquière. It is still being developed but is already available for use by anyone; its documentation is available at https://jgires.github.io/fonctionr/.

13. 46 % of students in the sample live with their parents.

14. HORECA is the acronym used to designate the hotel, restaurant and café industry.

15. When a student is enrolled in more than one degree programme, the average used is the average of the averages for each programme, weighted by the number of credits in each.

16. This is actually the distribution in the form of a density function, which can be interpreted as a smoothed histogram.

17. In order to define the socio-professional position of parents, the father's employment status was preferred to that of the mother, as the latter was much more likely to be a homemaker, making the position less socially discriminating. When the father's situation was unknown or the father was absent, the mother's situation was used. The socio-professional classification used was inspired by the Goldthorpe class scheme [Brousse, 2010]; it is constructed on the basis of occupation status (employee, company manager, self-employed, homemaker, etc.) and the title of the occupation according to the ISCO. Operationalisation was guided by the procedures developed as part of the European ESeC classification project: https://www.iser.essex.ac.uk/archives/esec.

18. When answering the questionnaire, students were given the choice of the order in which they described their parents. The country of birth is that of the first parent entered, regardless of gender.

19. The modalities of the simplified variables are self-explanatory, except for the socio-professional position of the parents: intermediate professions refer to middle management and higher-level employees; low-skilled workers & unemployed refer to lower-level employees, low-skilled workers and unemployed (receiving unemployment benefits, homemaker or ill).

20. The survey asked whether students had been subjected to humiliating remarks during their time at ULB, according to different criteria. I have grouped together under the term “racist remarks” humiliation related to skin colour, origin or nationality and/or religion.
ABSTRACTS

The aim of this article is to document the current reality of inequalities in university education, focusing on the way in which purely material difficulties condition the academic performance of students. The statistical analysis is based on survey data collected at Université libre de Bruxelles (ULB); it has the particularity of starting from the living situation of students and categorising them according to the hardships they experience. The survey was carried out during the COVID-19 pandemic, highlighting the difficulties of those in the most precarious situations and thus shedding light on the question of living conditions. The analysis shows that there are indeed significant academic inequalities between students according to their living conditions: the greater the hardship, the lower the students' marks. Students who experience the greatest hardships are more likely to come from modest backgrounds, but we can see that hardship can exist independently of social and family background, indicating that material constraints are an obstacle in themselves to the successful completion of higher education. The analysis also reveals that there are many inequalities with respect to university education, which stem from different social relationships: in particular, at equal social levels, ethno-racial inequalities exist.

Cet article a pour objectif de documenter la réalité actuelle des inégalités dans l'enseignement universitaire, en focalisant son attention sur la manière dont les difficultés proprement matérielles conditionnent les performances académiques des étudiant·es. L'analyse statistique est réalisée à partir de données d'enquête récoltées à l'Université libre de Bruxelles (ULB) ; elle a la particularité de partir de la situation de vie vécue par les étudiant·es, en les catégorisant selon les privations qu'ils et elles subissent. L'enquête a été réalisée pendant la pandémie de covid-19, accentuant les difficultés des plus précaires et créant ainsi un effet de loupe sur la question des conditions de vie. L'analyse montre qu'il existe effectivement des inégalités académiques marquées entre étudiant·es selon leurs conditions de vie : plus les privations sont grandes, plus les points des étudiant·es sont bas. Les étudiant·es en plus grande privation sont plus souvent d'origine modeste, mais on observe que les privations peuvent agir indépendamment de l'origine sociale et familiale, indiquant que les contraintes matérielles constituent un obstacle "en soi" à la bonne conduite des études supérieures. L'analyse révèle par ailleurs que les inégalités face à l'institution universitaire sont multiples, et relèvent de rapports sociaux différents : il existe notamment, à niveau social égal, des inégalités proprement ethnoraciales.

Het doel van dit artikel is om de huidige situatie omtrent de ongelijkheden in het universitair onderwijs te documenteren. Daarbij gaat de aandacht vooral naar de manier waarop specifiek materiële problemen bepalend zijn voor de academische prestaties van studenten. De statistische analyse wordt uitgevoerd op basis van onderzoeksgegevens die verzameld werden aan de Université libre de Bruxelles (ULB). Wat deze analyse zo bijzonder maakt, is dat er wordt uitgegaan van de leefomstandigheden van de studenten, waarbij ze volgens hun ontberingen in categorieën onderverdeeld worden. Het onderzoek werd uitgevoerd tijdens de COVID-19-pandemie, die de problemen van de meest kwetsbaren nog verergerd heeft en de kwestie van de leefomstandigheden uitvergroot heeft. Uit de analyse blijkt dat er wel degelijk opvallende academische ongelijkheden bestaan tussen studenten naargelang hun leefomstandigheden: hoe groter de ontberingen, hoe lager de punten van de studenten. De studenten met de grootste ontberingen hebben vaker een bescheiden achtergrond, maar we stellen vast dat er zich ontberingen kunnen voordoen los van de sociale en familiale achtergrond. Dit wijst erop dat de materiële beperkingen op zich een obstakel vormen om hogere studies met succes af te ronden.
De analyse brengt ook aan het licht dat er meerdere ongelijkheden zijn op het vlak van universitair onderwijs en dat die ongelijkheden onder verschillende sociale verhoudingen vallen. Zo valt op dat er zich vooral bij een gelijk sociaal niveau specifiek etnisch-raciale ongelijkheden voordoen.

## INDEX

**Keywords:** education, social inequalities, racism, youth, poverty

**Trefwoorden:** onderwijs, sociale ongelijkheden, racisme, jeugd, armoede

**Mots-clés:** enseignement, inégalités sociales, racisme, jeunesse, pauvreté

## AUTHORS

### JOËL GIRÈS

Joël Girès has been a sociology researcher since 2011. He was awarded a doctorate in sociology of science in 2022. The same year, he became a researcher at the Observatoire de la Santé et du Social (Vivalis), working on issues relating to social and health inequalities. He and his friends and colleagues founded the Observatoire belge des inégalités (www.inegalites.be).
joel.gires[at]gmail.com

## TRANSLATORS

### JANE CORRIGAN