Understanding the socio-economic distribution of multiple deprivation: An application of self-organising maps

In this paper we seek to contribute to recent efforts to develop and implement multi-dimensional approaches to social exclusion by applying self-organising maps (SOMs) to a set of material deprivation indicators from the Irish component of EU-SILC. The first stage of our analysis involves the identification of sixteen clusters that confirm the multi-dimensional nature of deprivation in contemporary Ireland and the limitations of focusing solely on income. In going beyond this mapping stage, we consider both patterns of socio-economic differentiation in relation to cluster membership and the extent to which such membership contributes to our understanding of economic stress. Our analysis makes clear the continuing importance of traditional forms of stratification relating to factors such as income, social class and housing tenure in accounting for patterns of multiple deprivation. However, it also confirms the role of acute life events and life cycle and location influences. Most importantly, it demonstrates that conclusions relating to the relative impact of different kinds of socio-economic influences are highly dependent on the form of deprivation being considered. Our analysis suggests that debates relating to the extent to which poverty and social exclusion have become individualized should take particular care to distinguish between different kinds of outcomes. Further analysis demonstrates that the SOM approach is considerably more successful than a comparable latent class analysis in identifying those exposed to subjective economic stress.     

Societal Gender Inequality as Moderator of the Relationship Between Work–Life Fit and Subjective Well-Being: A Multilevel Analysis Across European Countries

Social Indicators Research - Social well-being of person who works in social services as well as hospital staff has a large effect on care quality and organizational efficiency. The aim of this...     

Mapping Patterns of Multiple Deprivation and Well-Being using Self-Organizing Maps: An Application to Swiss Household Panel Data

The aim of this paper is to propose multidimensional measures of deprivation and wellbeing in contemporary Switzerland, in order to overcome the limitations of standard approaches. More precisely, we have developed self organising maps (SOM) using data drawn from the 2009 Swiss Household Panel wave, in order to identify highly homogeneous clusters of individuals characterized by distinct profiles across 44 indicators of deprivation and well-being. SOM is a vector quantiser that performs a topology-preserving mapping of the k-dimensional input data to a two-dimensional, rectangular grid of output units, preserving as much as possible the information contained in the original input data. “Topology-preserving” means that, when an SOM is properly developed, units that are close in the output space are also close in the input space. Our results suggest that the SOM approach could improve our understanding of complex and multidimensional phenomena, like those of well-being, deprivation, vulnerability, that show only a partial overlapping with standard income poverty measures.