MODULE 2 - WHAT IS SCHOOL SEGREGATION
Segregation is one of the hardest forms of separation. The negative nuance we commonly attribute to the concept of segregation is due to its link with inequality:
on the one hand, segregation rises from inequalities; on the other, segregation freezes inequalities, exacerbating them. In this module, we observe school segregation as a pivotal factor of inequality dynamics.
Despite education system reforms of the last decades aimed to reduce inequality of opportunities, the introduction of a competitive market model to education systems encourages forms of segregation.
We need specific tools to observe and to tackle school segregation, as well as assessing this phenomenon in its structure.
Objectives of the module: This module provides a short review of the definition of school segregation. Starting from the history of the concept, the module aims to give basic instruments to observe and analyse the phenomenon. In particular, the module objectives are:
- To provide a conceptualization of school segregation
- To explore the main ways to assess and measure school segregation
- To define a toolbox for school segregation observation
Outline of the module: This module is structured in three Units, all related to the three mentioned objectives.
Unit 2.1. Definition of school segregation, offers a short description of school segregation. Starting from the definitions more frequently found in literature, we provide a description of the phenomenon of school segregation, considering its main drivers and shapes.
Unit 2.2. Measuring school segregation, helps comprehend the segregation indexes often used in research. Here, we explain the logic behind these indexes, as to help the reader interpret their meanings more easily.[XB2]
Unit 2.3. Taking stock: assessing school segregation in your territory, concludes the module by providing instructions useful to analyse and interpret school segregation in your city.
Collet-Sabé, Jordi. (2019). Understanding school segregation: patterns, causes and consequences of spatial inequalities in education: edited by Xavier Bonal and Cristián Bellei, London, Bloomsbury, 2018, 255 pp., ISBN 978-1-35-003351-1. British Journal of Sociology of Education. 40. 1-5. 10.1080/01425692.2019.1656909.
Parable of the Polygons https://ncase.me/polygons/
UNIT 2.1. Definitions of school segregation
The path from urban segregation to school segregation is short. If urban segregation can be defined as the unequal distribution of social groups between neighbourhoods of a city, school segregation can be thought of as the unequal distribution of different groups of students in schools within a school system. Here, the focus isn’t on the concept, but on its units of analysis.
The space of segregation
Whether it is the city or the school, segregation arises in defined portions of the territory of analysis compared to the whole territory. Even though the concentration of a group can characterise a specific portion of the territory, segregation can only be observed taking all the portions composing the territory into account. Hence, a school can be more or less segregated in respect to other schools. According to the scale of our interest, we can define the school system as the schools of a city,
or as the schools of a region. Alternatively, we could be interested in the segregation regarding a specific school sector, such as the public or the private school system. The point is that we select the units of analysis to be compared, and the scale of our observation.
The object of segregation: from a category to a social group
In the absence of explicitly discriminatory policies, segregation can be seen from two main perspectives:
Self-segregation, as a product of the behaviour of specific groups (such as social elites or ethnic groups) that want to separate from other social groups; Systemic segregation, due to general dynamics of distribution of the population in the school system.
Segregation can be the result of an intentional strategy, or it can be an unintended effect. In the first case, homogeneous social groups tend to separate themselves from other social groups to mark their identity or obtain selective access to what they believe is an “adequate” education. This is common in minority groups settled in heterogeneous urban contexts that want to preserve their identities, languages and cultures. Moreover, self-segregation can be the result of identity strategies aimed to
separate elite groups from the others. Most of the times this strategy targets private schools, but in specific contexts we can find identity strategies involving public schools located in rich or super-rich neighborhoods. On the other hand, segregation can be the result of avoidance strategies carried out by middle class families who want to avoid schools characterized by high social or ethnic heterogeneity. Their residential or school choice (if allowed) may contribute to self-segregate themselves
into the chosen schools and to segregate the others in the rest of the school system. The combination of both strategies – elite groups self-segregating in elite schools, and middle-class groups avoiding ethnic or socially mixed schools – may pave the way for high levels of segregation for the overall school population.
Segregation is, however, often an unintended consequence. It affects social groups with only limited choice concerning housing and school.
In countries where school choice is not allowed (see below), segregation is always the unintended reproduction of territorial segregation.
In such cases, the distribution of students mirrors the residential distribution of the population. The housing strategies of the richest families
can reinforce the effect of spatial segregation. When school choice is allowed, unintended segregation is the result of the choice made by some groups.
There is strong evidence that the poorest groups as well as ethnic minorities are most affected by this kind of segregation (See Module 3).
Segregation becomes a social issue when segregated homogeneous social groups are characterized by disadvantage due to socioeconomic status, race, or ethnic status.
Know more about this topic
Boterman et al. (2019) School segregation in contemporary cities: Socio-spatial dynamics, institutional context and urban outcomes.
In Urban Studies, vol. 56(15), 3055-3073,
The self-segregation dynamic of elites in suburban areas of US cities inspired the idea of the ‘white flight’. This is also used to describe segregation dynamics in Europe, when the concentration of social groups in specific areas is the result of physical movements or commuting of these groups. Depending on allocation rules of a school system, the ‘white flight’ dynamic in school-segregation arises due to the choice of middle and upper-class households to opt out of the schools of their catchment area or to opt out of the public school system overall. In this sense, the choice of the right school becomes a foundational condition for the social reproduction of class advantage. In contexts without explicitly discriminatory policies or regulations, as in European Union countries, the most important distinction criteria at the base of segregation are the socioeconomic and ethnic status.
Nonetheless, segregation can also be based on gender, family structures and other cultural elements irreducible to ethnicity, such as aspirations or expectations from school experience.
On the one hand, as observed in the Joint Research Center (JRC) technical report on Immigrant background and expected early school leaving in Europe, immigrant student goals and expectations in education could not correspond to the goals and expectations of native pupils. While “their parents’ migration decision was often motivated by the search for better work and education opportunities for themselves and their children”, educational prospects aren’t always as important as work opportunities. On the other hand, inside such macro-groups, preferences may differ with respect to pedagogical perspective and other school characteristics, such as the artistic development and so on. Such differences could be more or less clear depending on the spatial organisation of cities and of the school supply. Uneven distributions of pupils could be observed in such neighbourhoods characterised by social and cultural mix, where different choices and preferences could emphasize distances that don’t exist on the spatial dimension.
Despite the fact that some European systems of public schooling date back to the 18th century, the diffusion and the extension of compulsory schooling is the object of reforms that took place mostly in the second half of the 19th and in the 20th century.
Main dimensions of such interventions rest on the definition of comprehensive school tracks and on public oriented school service and organization.
We can find several examples. In Italy, the establishment of compulsory primary school goes back to the State unification, in 1861, and to the extension of the Casato Law. According to the Law, primary education became a municipalities responsibility.
In 1962, after major reforms on school cycles, the lower secondary school, called “scuola media”, became compulsory and gives access to upper secondary schools and vocational secondary school. In Spain, the definition of the contemporary education system goes back to 1857,
and more precisely to the Moyano Act, which was the first attempt to implement the Constitutional right to the education (Constitution of Cadiz, 1812). On the one hand, the Moyano Act established compulsory education up to ten years old and only in some municipalities.
On the other hand, it consolidated private education, mainly provided by Catholic schools. Primary school became fully free in 1931, in the Second Republic period, but since the Civil War started in 1936, the project of a mass school system had to wait again.
In 1970, the General Act on Education and Financing of Educational Reform established a general education system based on a non‐discriminatory and full schooling for pupils aged between 6 and 14.
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A report on this work by Alexandre Chevalier here: https://journals.openedition.org/lectures/16292
In Norway, the attendance of Folkeskole (people’s school), established in 1827 and now replaced by Grunnskole, became mandatory for 7 years in 1889, and was extended to 9 years in 1969. Generally, schools in Norway have always been financed by public authorities, and there are very few private schools. Similarly, in the 1960s there was an extension of compulsory school in France (up to 16 years) and in Germany (Fed. Rep.) up to 9 years. As observed by Christelle Garrouste, the impact of these reforms concern both quantitative and qualitative dimensions. On the one hand, the ‘implementation of measures to ensure that all pupils would obtain a certificate of basic education’ improved the education attainment in most of Europe, increasing the quantitative impact of public schooling; on the other hand, the reforms of the second half of 20th century increased the quality of basic education, reshaping public school organization, the number of teaching staff, and recruitment modes. Such reforms played a crucial role in terms of education inequality reduction and reshaping. According to François Dubet, if on the one hand mass education put an end to classical inequalities based on great social and cultural categories, on the other, mass education also become the ground of new educational inequalities. New educational regulations and new complex sets of choices and strategies acted by the upper class families, reduced the results of mass education in terms of equality. To understand the difference, we have to consider the historical scenarios. The “classical inequalities” rested mostly on exclusion of a large part of the population from education. On the contrary, in a mass education context, most part of education inequalities take place within the educational paths in terms of duration, results, skills and, quality. Broadly, the combinations of these elements can affect the equality also in the range of a single education system.
As we can observe by data provided by Barro and Lee , also used by the UNDP in Human Development Report, since the 1820 the progression of enrolment in primary school ratio in Italy, Spain and Norway, followed trends sometimes differentiated for women (see graph in Fig. 1). In terms of years in total schooling for population aged 15-24, we had to wait to the 1980s to observe a complete reduction between the average years in total schooling for women and for the whole population in all the sample countries.
The women’s delay in terms of total schooling years is a way to observe how inequality takes place. Considering the most significant reforms of compulsory education duration since the Second World War in twelve European countries, Brunello, Fort and Weber recently discussed the impact of education path duration on earnings capability.
They provided evidence that, in a sample of European countries, “the effect of compulsory schooling laws on educational attainment is statistically significant for all but the top deciles of the distribution of male education (all but the very top for females).”
Know more about this topic
Global Education Monitoring Report. Inclusion and education: ALL MEANS ALL. Available at:
As they explained, “since these reforms have been targeted at the lesser educated, who typically belong to the lower earnings quantiles, the statistically significant effect of compulsory school reforms on individuals with higher educational attainment suggests that better educated individuals react to increases in compulsory schooling by raising their own attainment, possibly in an effort to maintain their educational advantage over the less educated, who are more directly affected by the reforms” (3). Despite the fact that in Europe the compulsory education duration varies from 9 to 13 years in total and concerns the whole population, without distinction among sexes, religions and ethnicity, the effect of reforms isn’t the same for all. The gender still matters, but it isn’t the only distinction criteria we should consider.
In the Figure 3, extracted by the last UNESCO report on inclusive education, we can see the difference in terms of attainment for Gender and Wealth distanced groups. While in most European countries the gender parity index suggest an approaching parity, we can’t say the same for the Wealth parity index.
As observed in the position paper fighting the school segregation, children with special needs, as well as Roma and Traveller children, are often enrolled in remedial classrooms and special schools , where they receive education with a reduced curriculum. Pupils taught in ‘specialized education do not usually obtain a recognized diploma and have limited access to secondary and higher education, also preventing the reintegration into mainstream education. The “entrapment logic” also affects pupils addressed to vocational paths as a result of educational tracking. In the next Modules, we will discuss main approaches in European countries on school tracking. For the moment we limit our considerations to the rigidity of separation dynamics.
As a reaction to new needs of the labour market, education systems of the richest countries have been introduced to the so-called vocational tracks, Vocational education and training (VET), in addition to general and academic ones. In a recent literature review on VET track mechanisms published on Nature, M. Ozer and M. Perc observed how despite some vantages in specific work contexts, “graduates of VET have fewer chances for higher education and prestigious professions” and less mobility opportunities between occupations. This is why the track based separation provides a “mechanism of social reproduction by diverting working-class students from higher education and prestigious professions”.
Know more about this topic
Council of Europe commissioner for Human Rights Fighting school segregation in Europe through inclusive education a position paper
Available at: https://rm.coe.int/fighting-school-segregationin-europe-throughinclusive-education-a-posi/168073fb65
European Agency Statistic on Inclusive Education – EASIE (2019) Dataset Cross-Country report
Available at: https://www.european-agency.org/resources/publications/european-agency-statistics-inclusive-education-2018-dataset-cross-country
The fragmentations reducing the impacts of inclusive and comprehensive school systems are nowadays the result of complex regulation puzzles aimed to guarantee the right to education merging private and public logic. In these terms, and, above all, in terms of impact on equality and segregation, the role of private schooling is pivotal in a large part of European countries.
In several European countries, such as Austria, The Netherlands and Denmark, the introduction and the extension of compulsory education overlapped with the statement of a double right. On the one hand, for private entities and for families it allowed establishing private and independent schools; on the other, it guaranteed the choice of the school which could better satisfy family preferences in terms of contents and teaching methodology. In other countries, the right to establish and to choose private schools has been stated in reforms in the second half of the 20th century.
At the moment, different combinations of principles and regulation schemes inform several forms of school demand (see graph below). On the one hand, public systems enrol the most part of European students in compulsory stages of the educational path (primary and lower secondary); on the other, the school attendance composition is strongly differentiated at a country level. The European average of private school attendance is 12%. Private schools host more than one pupil in four in the UK and in Spain, and more than one in two in Belgium.
Know more about this topic
Cristelle Garrouste (2010) 100 Years of Educational Reforms in Europe: a contextual database
Eurydice European Unit (2000) Private education in the European Union
Organisation, administration and the public authorities’ role
Reforms in the last decades of the 20th century strongly reshaped the private school sector. Firstly, educational quality became a criteria for private school to be recognized or subsided. Secondly, in the reorganization of European welfare system, the right to choose for users became a central issue. As result, the private/public boundaries became less significant, and subsidizing private services encouraged competition among public institutions.
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School Segregation Across the World: Has any Progress Been Made in Reducing the Separation of the rich from the Poor?
By G. Gutiérrez; J. Jerrim and R. Torres
The Journal of Economic Inequality (2020) 18:157–179 https://doi.org/10.1007/s10888-019-09437-3
Following this logic, we can easily understand the pivotal role played by school segregation. As underlined by the last report of UNESCO, socio‐economic segregation is a persistent challenge. The recent publication of OECD on immigrant education shows that more than two‐thirds of immigrant students attended schools where at least half the students were immigrants.
The same measure concerns the Spanish school system, while it increases in Italy and in Norway up to more than 70%. Another “analysis using PISA data showed that half of the students in Chile and Mexico, but less than one‐third in Scandinavian countries, would have to be reassigned schools to achieve a uniform socio‐economic mixture.” Data used to explore the segregation phenomenon shows that in recent years, socio-economic segregation has barely changed.
The Dissimilarity index (see next paragraph) calculated by Gutierrez et al (2017)[XB8] for a sample of countries all over the world, shows, on one hand, the distances between economic areas, and on the other, how school segregation is increasing in most parts of the countries Firstly, we can observe the distance between the three main blocks of countries. Mexico and Chile are the countries with the most segregated schools, clearly over the second block, where we can find a sample of European countries and the United States.
Finally, on the lowest part of the graph there are the trends of Northern European countries, with the lowest indexes. But the graph tells us more. Despite the fact that the Northern European countries started the new Century with a Dissimilarity Index significantly lower than the other countries, fifteen years later,
their indexes are strongly worst, reducing the distances from other European countries. Between 2000 and 2015, school segregation also increased in countries of the second block, with the exception of Italy and Germany. Mexico and Chile showed a longer decreasing tendency.
UNIT 2.2. Measuring school segregation
TYPES OF INDEXES
Our definition of school segregation offers a good summary of the phenomenon, but it doesn’t provide a clear measure to observe it. When is a concentration significant? Or, what does it mean that a concentration of a group deviates from the general average of the group distribution in the school system as a whole? Which numbers should we take into account? From a formal point of view, segregation can be considered as the degree to which two groups are separated from each other. This formal definition can be applied to any context, from the spatial and residential one, to the educational one. In 1988, Douglas S. Massey and Nancy A. Denton provided an interesting exploration of the way we can observe segregation.
They considered a specific dimension of separation, showing a specific form of segregation through a specific index. The five distinct dimensions of spatial variation are: evenness, exposure, concentration, clustering and centrality. In the case of school segregation, most part of studies and analysis is limited to the evenness and exposure dimensions.
Evenness can be considered as the differential distribution of two social groups in the schools of an educational system. Therefore, a group is segregated if it is unevenly distributed across the schools, which means that evenness is maximized when all schools have the same relative number of minority and majority groups we can find in the whole school system. As observed by scholars, evenness can’t be measured in any absolute sense, but it is scaled to some other group.
The most used index to observe the evenness is the dissimilarity index. In Figure 6 the graph compares the dissimilarity index for socio-economic condition measured since the 2000 to the 2015 in a sample of countries. As described by the authors who provided data, the index has been calculated defining two student groups identified by their socio-economic status. As the index used to summarize the socio-economic status provided by PISA data is continuous, the choice of the cutting-point is arbitrary.
In the graph in Figure 6, the dissimilarity index shows the evenness among pupils with a socio-economic status lower than the median (50%), and pupils with a socio-economic status higher than the median. The authors also provided the Dissimilarity Index calculated by cutting the distribution at 30% and 80%, with similar results. Whatever the choice, the “Dissimilarity Index ranges from zero to one. A value of zero indicates that the proportion of both groups in every school is equal to the proportions found in the population (i.e. there is no segregation).
In contrast, a value of one indicates that there is complete segregation of pupils, such that all schools only have one group of students represented. The dissimilarity index thus measures the percentage of students from a group that would have to change school in order for each school to have the same percentage of that group as is found in the national population” (161).
The main limitation of this index is that to be calculated, we need to compare two groups at a time. This is the reason why school segregation is also measured with the Gorard’s segregation index, which compares the share of a group in one school to the share of the school population on the whole population on the educational system (see the box 1).
Box 1. Let’s practice: Dissimilarity indexes
The general formula of the Dissimilarity Index (D) is where j and j’ are the groups to be compared, t is the total population of each group and the x is the population of each group in our unit of analysis.
As example, in the case of Dissimilarity index for Free School Meal eligible students in school our formula could be written as
To solve the equation, we have to start from the shares of the groups. In our example, we have to consider the number of the pupils eligible to the FSM in a school over the number of eligible students in the whole educational system population. Secondly, we have to calculate the share of the school population over the population of the whole educational system. The differences between the two shares of each school is finally summed and divided by two. The result is the Dissimilarity index for the FSM group.
Differently by the Dissimilarity index, the formula of Gorard’s Dissimilarity index is
As we can see, instead of the second group, the second term is defined by the share of the population of a school on the whole school system population.
The exposure dimension provides an interesting point of view on segregation.
It refers to the probability that a member of a group interacts with a member of another group.
As observed by Massey and Duncan, ‘rather than measuring segregation as departure from some abstract ideal of “evenness,” exposure indices attempt to measure the experience of segregation as felt by the average minority or majority member’ (p. 287).
From an empirical perspective, evenness and exposure dimensions are strictly correlated, but if in the evenness dimension the size of the groups can make a difference, this isn’t true in the case of the exposure dimension.
The main measure for exposure dimension is the isolation index.
Its result can be read as the probability for a pupils of a group to attend the same school of a pupil of another group (see the box 2).
Both indexes are widely used, so they allow to compare segregation measures in different contexts or periods, and they can be easily calculated. However, as observed above, they can represent only some parts of the segregation complexity and, above all, even if an index can describe a phenomenon, it can’t explain it.
Box 2. Let’s practice: isolation index
The general formula of the isolation index is
To better understand it, we can write it as it would be calculated in the case of FSM students:
Also in this case, to solve the equation, we have to start from the shares of the groups. In our example, we have to consider the number of the pupils eligible to the FSM in a school over the number of eligible students in the whole educational system population. Secondly, we have to calculate the share of the pupils not eligible over the whole school population. The product between the two shares of each school is finally summed. The result is the probability of the interaction between the two groups.
Here, some examples provided by Benjamin Forest (Dartmouth College) on residential segregation:
DESCRIBE OR DECIDE: HOW NUMBERS ARE IMPORTANT?
Born to describe, statistical indexes and indicators have been acquiring an increasingly significant role in policy making processes in the last decades. From the European level to the local one, more and more policy objectives are informed by statistical indicators. We can easily find several examples of this trend looking at labour policies, where rates, ratios, and shares often justify political choices, making the decision-making process more technical.
As much as knowledge in all its shapes is strictly linked to policy effectiveness, the temptation to reduce a phenomenon to its measure affects this virtuous linkage by reducing its convenience. This is particularly relevant in policy areas where the action field consists in several spheres of human behaviour, and where statistical approximations risk to simplify the phenomenon, reducing the impact of a policy to the mere increasing or decreasing of an indicator.
Mostly, such distortions derive from a sort of descriptive overload of indicators. In other words, we tend to attribute to a statistical indicator more than it can really say by the way it is calculated.
The more complex a phenomenon is, the less a single index can synthesise it. Sometimes we need more than one indicator; sometimes we should merge several knowledge forms. This doesn’t mean that indicators are useless. On the contrary, it means that indicators can be more useful the more we know them. Knowledge opportunities given by the statistical indexes on school segregation are a powerful tool for desegregation, if we know them.
UNIT 2.3. Taking stock: Assessing school segregation in your territory
ARE THE DATA WE HAVE THE DATA WE NEED?
As we observed, school segregation is a dynamic phenomenon. It changes over the time and space, both in terms of its causes and its target. In US literature, school segregation is often observed from a “race” perspective. In the European contexts scholars usually discuss school segregation as a result of discrimination based on gender, socio-economic status or cultural belonging, as well as on ability and health conditions. This doesn’t mean that in the US context segregation is only racially based. And it doesn’t mean that a system less segregated from a gender perspective is less segregated also from other perspectives. We observed a part of this heterogeneity in the last paragraphs, where school segregation has been discussed through the data provided by scholars and transnational bodies on gender, cultural belonging, health and socio-economic status. The results are complex. This is why we study a full toolbox, rather than a single index, for a complete assessment of the phenomenon.
We analyse this along the following five main dimensions:
- School population. Firstly, we have to know the composition of the school population, both in individual schools and in the education system. As we observed, school segregation is a phenomenon that arises from the distribution of pupils of differentiated groups, so the first field of interest is the differentiation criteria or, in other terms, the variables needed to identify the groups.
- School supply and the school territorialisation. Which kind of school in which neighbourhood is the first step, but in our assessment we have to consider the school capacity and the main characteristics of its endowment. This gives us the opportunity to identify factors that make a school more attractive than another.
- Segregation. As observed, school segregation can be the result of many factors (see next module for a deeper discussion). Some of its drivers can be based on inclusion/exclusion elements embedded in the school system, or in the territory, or based on allocation policies that produce more than one shape of school segregation. A full toolbox will allow policy makers to assess and explore all of these possibilities.
- Mobility. This dimension is strictly connected to the school system organisation. Starting from the allocation policies to the private school supply, the mobility of pupils could be a dimension to consider for the analysis of the relationship among territorial and school segregation.
- Results. The last dimension is the results of pupils. By “results” we mean the performance assessment, but other indicators can be included. The centrality of this dimension rests both on the role it plays in school segregation cause, and on the role it plays in terms of school segregation effect.
Finding reliable data is a challenge. On the one hand, the collection of meaningful data should derive from a strong institutional collaboration in order to collect and update information. On the other, the risk of stigmatization and labelling or of privacy intrusions has to be considered, in order to avoid unexpected effects of such analysis. Nonetheless, the effectiveness of a policy is strictly linked to its informative basis.
In this module we provided a short definition of School Segregation, and linking it to other dimensions of inequality.
In particular, we observed how, despite the democratic aims of the most important school reforms in Europe, school segregation still affects the educational systems, reducing the opportunity offered by inclusive education.
School segregation appears as a multidimensional phenomenon, acting on a wide range of social fractures. This is the reason why, in order to tackle it, we need to extend our knowledge instruments up to a complete toolbox, allowing us to cover its main dimensions.