Dave Griffiths

Dimensions and Boundaries: Comparative Analysis of Occupational Structures Using Social Network and Social Interaction Distance Analysis:

This paper analyses social interactions between detailed occupational positions as a means of exploring social and occupational inequalities. Two methods are employed: descriptive techniques of social network analysis, and a well-established modelling approach (the ‘CAMSIS’ method of ‘Social Interaction Distance’ analysis). New results on occupational connections are presented for four countries - the United States, Romania, the Philippines and Venezuela – illustrative of a range of socio-economic regimes. Our analyses use detailed occupational measures based upon census data from 2000 to 2002, and we also use data on educational attainment, cross-classified by occupational positions. A broad, singular dimension of social stratification is shown to be the principal element of the structure of social interactions between occupations, but the methods also reveal the social role of various boundaries in occupational interaction patterns (defined by work location, education, and gender). We argue that such distinctions imply that occupational data at a disaggregated level can provide a more thorough understanding of social structure than is observable using amalgamated occupational schemes.

Academic Influence amongst the UK Public Elite

This article examines the position of academics within UK quasi-autonomous decision-making. Data have been collected on 2858 individuals, sitting on the boards of 187 Westminster quangos, to assess which social groups and outside institutions hold influence on independent decision-making. These include 200 academics, sitting on 84 different boards. Analysis of the networks generated through mutual memberships of outside institutions shows academics are sitting in strategic positions within the quango sector. This article argues that higher academics have retained their high public position. It utilizes social network analysis to demonstrate that academics hold strategic positions within governance networks, signifying both political influence and associations with the social elite.

CAMSIS and the Analysis of Social Interaction Distance

This chapter introduces the CAMSIS approach to ‘social interaction distance’ (SID) analysis (Sect. 4.1). We discuss the background to the approach in Sect. 4.2 and theories that are associated with it in Sects. 4.3 and 4.4. Subsequently, Chaps. 5 and 6 turn to the empirical features of CAMSIS scales and the practical aspects of their construction.

Homophily and Endogamy

The phenomena of ‘homophily’ and ‘endogamy’ refer to the tendency of people, on average, to form social ties with others of similar circumstances. ‘Homophily’, which means the preference for similarity, is used in sociology to refer to similarities in circumstances between people who are linked by any form of social relationship (e.g. friendships, partnerships). The special case of homophily in marriage/cohabitation is usually referred to as ‘homogamy’. Patterns of social contacts within group boundaries are known as ‘endogamy’. ‘Endogamy’ in a literal sense refers to marriage/cohabitation within groups, but it is often generalised to other forms of relationship. It is well established that friendship and cohabitation patterns show homophily and endogamy consistently across societies and over time (e.g. McPherson et al. 2001; Kalmijn 1998; Mare 1991).

Exploiting Non-standard Dimension Scores and Network Structures in the Analysis of Social Interactions Between Occupations

The SID analytical approach involving occupations summarises social distance patterns through statistical dimension scores (e.g. Chaps. 4, 5, and 6). Other approaches of network analysis can also be used to summarise similar data on social interactions (e.g. Chaps. 7 and 8). The usual focus is on the most important elements of the interaction structure—for example, the first and most important dimension of the SID solution or the most influential patterns of network connections. Previously, we have also looked at social interaction data for large populations, such as countries. However, there are some interesting extensions in the options for calculating and exploring dimension scores and network structures. In this chapter, we discuss making more use of ‘subsidiary’ dimensions from the SID solution (Sect. 11.2), undertaking SID analysis on smaller population groups of particular interest (Sect. 11.3). and ways of using other network analysis tools to study sub-populations of special interest (Sect. 11.4).

Social Network Analysis of Occupational Connections

Social network analysis (SNA) can be thought of as any approach to analysis that focusses upon the role of social connections between units. Marin and Wellman (2011, p. 11) argue that ‘social network analysis takes as its starting point the premise that social life is created primarily and most importantly by relations and the patterns formed by these relations’. The forms of analysis of social connections between occupations that we have discussed previously could all be conceived of as examples of social network analysis, but in this chapter we look at analysing the same data using a range of analytical techniques that might be presented as the ‘classical’ tools of SNA.

Constructing CAMSIS Scales

In this chapter, we describe the construction of CAMSIS scales. We begin with a brief illustration of software code (Sect. 6.2). We then comment on the underlying data on social connections between occupations which are used (Sects. 6.3, 6.4, and 6.5), and some of the issues that emerge in relation to different ways of using data (Sects. 6.6, 6.7, and 6.8). Next, we cover the techniques of statistical analysis (Sect. 6.9). Lastly, we comment on ways of using the results (Sect. 6.10) and on options for undertaking the whole process in a more automated way (Sect. 6.11). We draw primarily upon approaches that have been used hitherto in the CAMSIS project. More materials and supplementary resources such as samples of software code can be found on the CAMSIS project webpages. We also stress that analysts have some autonomy when generating CAMSIS scales—the exact results of any particular scale estimation are likely to be contingent upon operational decisions and subjective judgements that are made during the process.

Occupational-Level Residuals and Distributional Parameters

In this chapter, we cover two further options in the statistical analysis of social interactions between occupations. One concerns the extent to which distributional parameters about the wider social structure can be used to provide alternative summary statistics concerned with social distance and occupational inequalities (Sect. 9.2). The other concerns scenarios where it can be useful to use ‘random effects’ models to explore occupation-to-occupation variations in relevant outcomes (Sect. 9.3).

Social Interactions and Educational Inequality

Hitherto we have focussed upon occupational positions, but in this chapter we explore the extent to which data on educational experiences can be introduced into the analyses of social interactions and social stratification. We explore whether we might get a different and more compelling result if we used data on educational experiences in addition to (or instead of) occupational data in the analysis of social interactions.

Measures of Social Stratification

At this point we describe some of the most influential measures of social stratification in current use, particularly those based upon occupations. We refer to ‘social stratification’ as a structure of social inequality that is defined in terms of the distribution of, or access to, consequential resources (cf. Therborn 2013, c4; Platt 2011, c1; Blackburn 2008). In the UK in particular, many writers use ‘social class’ and ‘social stratification’ interchangeably. However, to us ‘social stratification’ is a more generic concept that refers to a structure of inequality which could take any mathematical form, whereas a structure of ‘social class’ necessarily disaggregates the members of a society into a number of distinct positions—that is, classes (e.g. Grusky and Weeden 2006).