Mapping social inequality : the spatial distribution of early school leavers in Malta

Abstract

This study is focused on the spatial distribution of early school leavers and socio-economic inequalities in Malta. Early school leavers are defined as those individuals aged between 18 to 24 years, with a minimum of lower secondary education and not in further education or training (EUROSTAT, 2010). The objective of this study is to discover significant trends and patterns that might explain the high rate of early school leavers in Malta, using Geographic Information Systems to map the data available from the National Statistics Office. The software ArcGIS is used as a tool to capture, structure, manage, analyse and visualise the data so that trends, patterns and relationships can be investigated in more depth and displayed visually. This study utilises a quantitative methodology using secondary data (collected in the Census 2005) to create population maps that display the socio-economic information on all districts in Malta. According to this study, the Southern Harbour district shows the highest percentages of early school leavers, high rates of unemployment, low levels of education and schooling. Gozo ranks the highest in socio-economic inequalities, and offers high percentages for persons at risk-of-poverty, individuals with low income levels, and individuals receiving most social benefits. As a matter of fact, this study identifies a very high spatial correlation between early school leavers and socio-economic inequalities. Social polarisation has been detected in several districts, with the Western and Northern districts showing the lowest rates of early school leavers and socio-economic inequalities. A north-south geographical divide in Malta has emerged whereby districts were shown polarised not only in the perpetuation of several inequalities but also in occupation patterns, with higher percentages of blue collar workers in the south and white collar workers in the north. Another important finding was that most early school leavers in Malta are in employment. These youths are undertaking jobs that do not require a tertiary level of education; in sectors with a larger constant demand for manpower, such as tourism or employed within family businesses. The spatial analysis maps designed and presented in this research have proved to be highly efficient in revealing patterns. The geographical analysis presented on socio-economic inequalities and early school leavers help identify more clearly districts which require further attention in terms of policy and investment in education. My discovery of associations between selected socio-economic variables and early school leavers in Malta can therefore help policy to make the required informed decisions.