• 1 The reason is that the level of education of parents is a variable which is easier to collect and u (...)

2This 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].

• 2 CPAS, or Centres publics d'action sociale, are municipal bodies which – under certain conditions – (...)

3This 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.

• 3 This survey was carried out on the initiative of the Observatoire de la vie étudiante at ULB. I wou (...)

4Based 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].

• 4 The resemblance of the sample to the study population was checked for known socio-demographic varia (...)

5The 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.

• 5 Grants are not available to them unless they have been in the country for 5 years, and for people w (...)
• 6 Foreign students from sub-Saharan Africa, the Maghreb and Asia are practically only registered at m (...)
• 7 This does not mean that the study conditions of foreign students are not important. 26 % of student (...)
• 8 In this article, when I speak of ethno-racial inequalities, I am referring to the social relations (...)

6One 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.

• 9 See the explanatory pages of the survey on the Eurostat website: https://ec.europa.eu/eurostat/fr/w (...)

7The 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.

• 10 This distribution should be interpreted with caution: it is a univariate statistic, and therefore h (...)
• 11 The number of students in the categories of hardship varies slightly between the different analyses (...)
• 12 Most of the results and graphs presented in this article were produced with fonctionr, a package fo (...)
• 13 46 % of students in the sample live with their parents.

8In 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.

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

10As 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.

• 17 In order to define the socio-professional position of parents, the father's employment status was p (...)
• 18 When answering the questionnaire, students were given the choice of the order in which they describ (...)

15Of 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.

• 19 The modalities of the simplified variables are self-explanatory, except for the socio-professional (...)

16It 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).

• 20 The survey asked whether students had been subjected to humiliating remarks during their time at UL (...)

19An 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.