SRHE Blog

The Society for Research into Higher Education


Leave a comment

Free higher education in Syria and inequalities

by Oudai Tozan

HE and inequality

The debate over whether higher education (HE) serves as a vehicle for social mobility that nurtures meritocracy or as a mechanism for social reproduction that reinforces and exacerbates inequalities in society has persisted for some time. The first perspective regards HE as a meritocratic, achievement-based system of stratification that selects and allocates individuals to societal roles based solely on their merit (in line with Émile Durkheim’s theories). Conversely, the second viewpoint sees education as a means that perpetuates social stratification and the cultural hegemony of the elite (reflecting Bourdieu’s perspective). This phenomenon occurs because students’ socio-economic backgrounds significantly influence their access to, decisions regarding, and success within HE.

To mitigate the impact of socioeconomic background on individuals’ educational opportunities, a movement of research and activism spans from South America to Africa and the Far East, advocating for free HE. To investigate this claim, I examined the situation in Syria, which has consistently asserted that it possesses a meritocratic HE system aimed at fostering societal equality through the provision of free public HE for all since the 1970s. I analysed the Ministry of Higher Education (MoHE) database for 15 academic years, from 2001 to 2015. This dataset encompassed information on student access and graduation rates, categorised by type of education (public, private, higher institutes, and technical institutes), education level (undergraduate and postgraduate), gender (male and female), city, faculty, and specialisations. This analysis revealed various forms of inequality, specifically class-based inequalities, city-based inequalities, and gender-based inequalities.

Class-based inequalities

Although every citizen in Syria who finishes school can access free public HE, many students from high socio-economic backgrounds choose private HE to obtain better education or to pursue specific courses unavailable in the free public tracks. An analysis of the data reveals that the graduation rate in private institutions is almost double that of public institutions. One of the reasons behind this discrepancy in graduation rates between free public HE and private HE is the lack of funding for free public HE. Public university students suffer from a high student-teacher ratio (in some cases, 140 students per teacher) and poor infrastructure compared to the low student-teacher ratio (around 20 students per teacher) and better infrastructure in private universities. Furthermore, inadequate funding for free public universities has led qualified lecturers to prefer teaching at private institutions. This has widened the inequality between public and private HE institutions, as students with the financial capacity to access private HE learn from the most qualified teachers in Syria and receive the best knowledge available.

City-based inequalities

Although Syria has 14 cities, during the analysis period (2008–2013), it had only 5 free public universities located in 5 different cities. These universities have small branches or centres in all Syrian cities, offering limited course options. This design of the HE system has neglected some cities in Syria, leaving them without a proper educational framework. Having only one large university in select cities advantages students who reside in those areas, as they do not endure the added financial and mental pressures that students from other cities face to access education, such as paying for accommodation, living away from home, and travelling to see their families. Consequently, many students from cities without a university may encounter additional barriers to accessing HE, negatively affecting their academic, professional, and personal opportunities and choices. This could explain why cities like Damascus, Homs, and Latakia (where universities are located) are consistently overrepresented in HE, while students from Hama, al-Hasakeh, and al-Rakka (which lack universities) are consistently underrepresented.

In addition to the inequality of access to HE, city-based inequalities also encompass disparities in accessing the various specialisations and faculties offered by HE. This is further exacerbated by the sector’s design as not all faculties or specialisations are available at every university or branch. For instance, undergraduate media studies are solely taught in Damascus. Although Damascus constitutes only 8.75% of the Syrian population, students from Damascus account for 23.9% of the total number of media students. This representation is nearly three times their percentage of the overall population. This significant overrepresentation of students in certain courses occurs at the expense of those from other cities who are unable to access these courses and faculties because they are not available in their localities. This trend of unequal access to specialisations applies to numerous disciplines (eg Pharmacy, Dentistry, Medicine, Arts, IT, Mechanical Engineering, and Architecture). In each of these specialisations, students in the cities where the courses are taught have a distinct advantage over students from other cities in terms of access.

Gender-based inequalities

Officials in the Syrian HE sector have consistently celebrated the progress they have made, asserting that free HE has eliminated gender-based inequality by achieving near parity in enrolment rates. Although noticeable progress has indeed occurred, this claim does not hold up under scrutiny as it obscures other gender inequalities affecting certain groups within the population.

An analysis of the database reveals that, while there is no overarching gender gap in the sector, apart from in undergraduate public universities, disparities exist across all other educational tracks. Moreover, the higher the level of education (Master’s, PhD, etc), the more pronounced the gap becomes. The analysis further indicates that gender-based inequalities extend beyond females’ access to specific tracks and impact female academic representation within the sector. A 14-year average shows that female teachers constitute less than 25% of the total teaching staff in the sector. However, in lower-paid and less prestigious roles, such as technical and administrative positions, females occupy more jobs than their male counterparts (57%).

Conclusion

Simply offering free HE does not address the broader socio-economic inequalities that limit people’s opportunities in HE. Assuming that free HE will foster equality in society presumes that everyone has an equal capacity to access education. This paper demonstrates that HE, if not paired with an inclusive sectoral design, increased funding, and a comprehensive strategy to alleviate socioeconomic inequalities, will persist as a site of social reproduction that creates and exacerbates disparities within societies, even if provided at no cost.

Dr Oudai Tozan recently finished his PhD at the University of Cambridge, researching the potential role of exiled Syrian academics and researchers in rebuilding the higher education sector of Syria. This blog is based on an article published in Policy Reviews in Higher Education: Tozan, O. (2024) ‘Peeling the multiple layers of inequalities in free higher education policies’ (online 12 July 2024).  

https://www.syria-education.com/

https://www.linkedin.com/in/oudai-tozan/


Leave a comment

Deprivation data: Introducing a new UK-wide area-based measure

by Tej Nathwani

Introduction

The 2020s will be a pivotal period in determining the UK’s economic future. That’s the primary message of a recent report published by the Resolution Foundation and Centre for Economic Performance at LSE. While major events such as the pandemic and Brexit have undoubtedly played a part in this, there are also longer-term factors that have contributed to the country reaching this position. Examples noted by the researchers include stagnant productivity levels, large disparities in economic performance between areas and inequalities in our education system.

Naturally, one of the questions being increasingly asked of the UK higher education sector is how it is helping to resolve some of the latter issues. Yet being able to tackle these matters successfully, as well as understand the outcomes from various interventions, requires the provision of suitable data. As the body responsible for the collection and dissemination of information about UK higher education, HESA has a role to play in supplying appropriate variables and statistics to our users that support them in their decision-making. Hence, the past few years have seen us develop new fields designed to be relevant and valuable in meeting the current needs of our customers. Across two separate blogs we will be outlining what these are and the potential value they can deliver. In this first piece we begin with a focus on our work relating to socioeconomic disadvantage.

The uses of data on deprivation in higher education

One of the ways in which providers seek to improve equality of opportunity in education is through outreach activity. These are initiatives that aim to raise aspiration and attainment among those from disadvantaged backgrounds, as well as helping to inform them of the potential benefits that studying for a degree can offer. Area-based data on deprivation will typically be used in two ways. Firstly, as part of the eligibility criteria that an individual must meet to participate (for example, at Surrey). Secondly, it can help providers determine the areas of the country which they believe would be most useful to target given their strategic ambitions (for example, at King’s College London).

The current problem

The most commonly used area-based measure of disadvantage across the sector in each of the four nations is the index formed from the Indices of Deprivation. However, while this is especially effective in capturing deprivation in major urban areas, it is known to be less useful in identifying this in rural locations. For example, Na h-Eileanan Siar in Scotland has no localities that emerge in the bottom quintile of the Scottish Index of Multiple Deprivation (SIMD), despite income levels being below the national average. (Indeed, local government looking at poverty in the area highlight that ‘There are difficulties in using the SIMD in rural areas. Areas such as the Outer Hebrides are sparsely populated, socially heterogeneous and less sensitive to area-based measures such as SIMD. This can lead to a situation where households in rural areas are omitted from policy and targeting by national interventions designed to address poverty and inequalities’.) Furthermore, the size of the areas used to derive the index can also make it difficult to fully understand the levels of deprivation within localities. For example, there may be pockets within a zone that are experiencing higher levels of disadvantage compared with other vicinities, but the use of a more aggregated geographic domain can lead to this being masked. The consequence of this for the higher education sector is that there may be some prospective students who live in deprived neighbourhoods, but due to the limitations of existing data, find themselves unable to participate in outreach activity (eg as a result of not meeting the eligibility criteria or providers not targeting their place of residence).

Comparability is also an important aspect of high-quality statistics. Each nation of the UK, however, adopts a different approach in generating its index from the Indices of Deprivation. This means it is not a UK-wide variable and does not enable statistics to be evaluated across nations. Both the Office for Statistics Regulation and the latest State of the Nation report by the Social Mobility Commission (see p20) have highlighted this as an existing data gap that inhibits our understanding of wider societal trends in social mobility.

A potential solution

The question we therefore asked ourselves was ‘Can we create a UK-wide area-based measure of deprivation that can also address some of the drawbacks of existing indicators?’. To do so, we relied upon the 2011 Census, given the questions asked across the nations are harmonised as far as possible, meaning a UK-wide metric can be created. Data are also released at ‘output area’ level (output areas are often referred to as ‘small areas’ in Northern Ireland), which is a smaller level of geography than is used for the Indices of Deprivation. Output areas will typically contain less than 500 individuals.

With earnings data not available in the Census, our measure of deprivation was derived using the qualifications and occupations of residents in output areas, given these two factors are key determinants of low income. Having generated this, and to understand the potential value it could bring, we compared the bottom quintile of our measure to the equivalent group in the index produced from the Indices of Deprivation (ie the most deprived neighbourhoods). In each of the four nations, we found that our measure picked up a greater proportion of rural areas, albeit to varying degrees. Furthermore, when looking at those output areas that emerged in the lowest fifth of our measure, but a higher quintile of the index developed using the Indices of Deprivation, we observe that the most prevalent localities are based in local authorities/council areas/local government districts where there appear to be lower levels of economic activity (eg County Durham in England, North Lanarkshire in Scotland, Rhondda in Wales, as well as Armagh City, Banbridge and Craigavon in Northern Ireland).

Concluding thoughts

In summary, our measure does seem to overcome some of the existing shortcomings of area-based indicators of deprivation. Over the next few years, we shall therefore be looking to supply the measure to users in an accessible format, alongside updating it using information from the most recent Census. As well as supporting equality of opportunity, if the measure can help to raise participation and skill levels in some of our most deprived neighbourhoods, there is also the possibility that this will assist with reducing spatial disparities in output. For example, the study by the Resolution Foundation and the Centre for Economic Performance notes that the ability of the Shared Prosperity Fund to successfully increase growth may well depend on the levels of human capital in the area. Through upskilling local residents living in disadvantaged localities, providers may therefore be able to facilitate the creation of the conditions needed for growth-enhancing initiatives to succeed. Of course, this rests on the assumption that these areas do not subsequently see residents move to other parts of the country. Understanding the geographical mobility of graduates will thus be the topic of our next blog.

Read more about our measure, its correlation with income and how it compares to the Indices of Deprivation https://www.hesa.ac.uk/insight/08-11-2022/new-area-based-measure-deprivation-summary.

Feedback on our measure of deprivation is most welcome. Please send this to pressoffice@hesa.ac.uk.

To be kept updated on our publication plans and latest research releases, please join our mailing list.

Tej Nathwani is a Principal Researcher (Economist) at HESA, which is now part of Jisc.

Simon Marginson


Leave a comment

Equality of opportunity: the first fifty years

By Simon Marginson

The article below is abridged from the keynote address given at the SRHE’s 50th Anniversary Colloquium at Church House, London on June 26th 2015.  The full text of this keynote address is available via www.srhe.ac.uk/downloads/SimonMarginsonKeynote.pdf 

Thomas Piketty’s Capital in the Twenty-first Century (2014) clarifies  the distinction between (1)  societies in which incomes are relatively equal and/or there is a high degree of middle class growth and social mobility, which includes (albeit in different ways and for rather different reasons) both the Scandinavian countries and emerging East Asia; and (2) societies like the United States or the UK that are relatively closed in character, with highly unequal wage structures, growing capital concentrations, and static middle classes that are under considerable pressure to defend their past-gained economic and status positions. Continue reading