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Title: Reconsidering disadvantage in the United States : an application of social exclusion to 'big' American data
Author: Green, Dominique Lashari
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2020
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Poverty and disadvantage in the United States are commonly defined in terms of low income. Via this measure, in 2015, over 40 million people were deemed as poor. This definition and subsequent measurement neglect the multidimensional nature of the phenomena. It has been acknowledged that this reductionist measure is insufficient to capture many dimensions of hardship beyond the economic. However, there have been few attempts at quantifying multidimensional disadvantage in the United States. The aim of this thesis is to quantify multidimensional disadvantage by applying the concept of social exclusion to ‘big’ American data, the United States Census Bureau-produced American Community Survey (ACS) Public Use Microdata Sample (PUMS) file for 2015 that contains over 2.3 million sample members. Social exclusion, as a concept, theoretically addresses many of the limitations of the official measure. In particular, it offers a multidimensional conceptualisation of disadvantage. This concept, however, is substantially under-researched in the United States. In order to apply the concept to a context in which it is rarely used, social exclusion is measured and defined based on the theoretically derived framework, the Bristol Social Exclusion Matrix (B-SEM). This framework identifies three interconnected domains of social exclusion: resources, participation and quality of life. The substantive and methodological objectives of this thesis are threefold: 1) to empirically derive the factors of disadvantage in the United States by applying B-SEM to indicators found within the ACS PUMS, 2) to assess the relationship between sociodemographic variables and the dimension(s) of disadvantage, and 3) to explore state-level variation in disadvantage across the United States. An exploratory factor analysis was used to empirically derive the factors of disadvantage in the United States. The results produced three distinct factors: ‘labour force participation,’ ‘economic security,’ and ‘marriage as a social resource.’ This highlights that disadvantage in the United States is indeed multidimensional, with income representing one component of one factor. Therefore, a focus on a lack of income is incomplete to fully understand disadvantage in the United States. Six ordinary least squares (OLS) multivariate regression models were used to analyse the relationships between the sociodemographic characteristics, age, race, gender, and citizenship status and intersectional characteristics (the intersection between gender and race). In the non-intersectional models, it was found that these characteristics explain more variation in the ‘labour force participation’ model, compared to the other two dimensions. In the intersectional model, however, over three times the variation is explained in the ‘economic security’ model, compared to the other two dimensions. The results highlight that different individuals do experience disadvantage differently, showcasing the importance of recognising and addressing multiple forms of disadvantage. Twelve multilevel models were used to assess if there was variation in the dimensions of disadvantage across the United States, if that variation held controlling for sociodemographic characteristics, and if the relationships between the individual characteristics and the dimensions of disadvantage varied across states. The models demonstrated that there was state level variation in each dimension of disadvantage across the United States and that variation persisted once individual characteristics were controlled for. In addition, it was found that the effect of gender varies significantly across states for each dimension of disadvantage. These results highlight the importance of context in understanding disadvantage and shed light on an important role the state plays in reducing and preventing disadvantage. These results have important implications for policies designed to alleviate disadvantage in the United States. In addition to expanding all income-based benefits at least to individuals who are 250% above the federal poverty line, state governments should promote the provision of health care to all members of their respective populations and provide incentives that encourage educational attainment.
Supervisor: Norris, Paul ; Koslowski, Alison Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: big data ; poverty ; multidimensional poverty ; multilevel modelling ; intersectionality