Although networks are made up of weak social ties, they can be a powerful resource

If ‘social capital’, conceptualized here as the valued resources embedded in social networks, is as important for status attainment as many scholars believe (Lai et al., 1998, Erickson, 2001b, Lin, 2001), then knowing who has more of it and where it comes from is of critical concern (Small, 2009). The question is not whether social capital is unevenly distributed – we know it is (Lin, 2000). Rather, we need a better understanding of how social capital is unevenly distributed and why.

The literature on social capital yields important insights, showing that powerful gender and ethnic groups (such as men and whites) have greater access to social capital than women and minorities (Lin and Ao, 2008, McDonald et al., 2009, Son and Lin, 2012). Scholars also show that individuals’ unequal access to social capital has much to do with their unequal access to organizations, such as schools (Ball, 2003), workplaces (Ibarra, 1995) and childcare centres (Small, 2009), as these constitute critical arenas of social capital formation. Both strands of scholarship notwithstanding, there are at least three unanswered questions concerning unequal access to social capital:

First, in what complex ways do gender and ethnicity accompany social capital? If we treat ‘social capital’ as connections to different types of social ties – as Erickson (2001a, p. 324) recommends we do because ‘different aspects of networks are good for different outcomes’ – then we must work out which ascriptive categories go with which types of social capital. The current literature provides a hint: gender inequalities in social capital tend to be discussed in terms of men and women’s unequal access to forms of social capital such as ties to non-kin (Moore, 1990), weak ties (McPherson and Smith-Lovin, 1982), and ties to men (Erickson, 2004); by contrast, ethnic inequalities in social capital tend to be discussed in terms of ethnic groups’ unequal access to people in certain occupations (i.e., knowing a doctor, lawyer; see Lin and Erickson, 2008), well-educated people (Wilson, 1987), and people from a dominant ethnic group (Moren-Cross and Lin, 2008). Yet the fact that different kinds of ascriptive categories have different kinds of social capital inequalities has not been highlighted or explained.

Second, we need an intersectional view of network inequalities. Scholars caution that while gender and ethnicity are unique categories in their own right, every person has simultaneously a gender, ethnic and class position. Together, these constitute markers of a composite identity affecting individual life chances (Collins, 1993, Glenn, 1999, Acker, 2006, Choo and Ferree, 2010). Feminist scholars began their work theorizing about gender, but it soon became clear that gender was itself complicated by ethnicity: black-men rather than black-women were most frequently denied access to economic opportunities (Collins, 2004); white-men (relative to other combinations) enjoyed the greatest access to social capital (McDonald et al., 2009). Both examples illustrate the need for an intersectional analysis if we are to better understand the nature of social inequality, network or otherwise.

Third, while organizations are important arenas for the formation and maintenance of social capital (Feld, 1981, Small, 2009), there is a lack of research concerning which organizations generate inequalities in access to social capital and how they do so. From an organizational perspective, network inequalities may be reproduced in two ways: (1) gender and ethnic groups have unequal access to organizations, and thereby unequal access to social capital; (2) organizations may add social capital more efficaciously for one group of members than another. The first points to mechanisms that either grant or block access to organizational membership (here the tussle occurs at the boundary of the organization); the second points to mechanisms within the organizations themselves that allocate resources unequally among those who are already members. The latter implies an interaction effect and is novel for contemporary research in the sense that although we know networks arise in organizational contexts (Small, 2009), there is little known about the potentially differential rates at which organizations produce social capital among different categories of people.

By considering these three critical lacunae in the context of Singaporean data (collected in 2005) this study is able to answer the following three questions. Why do Chinese – as the dominant ethnic group (relative to the minority Malays and Indians) – have greater access to forms of social capital such as ties to well-educated people, wealthy people, and Chinese (but not ties to men or non-kin)? Why do men have greater access to forms of social capital such as ties to men, non-kin ties, and weak ties (but not ties to well-educated, wealthy, or Chinese people)? Finally, and more generally, why and how do ascriptive categorical forms of stratification such as gender and ethnicity produce such characteristic forms of organizational access and consequently such characteristic forms of network inequalities? Although the study looks at Singapore, it has wider significance, suggesting a complex intersection of ascriptive categories, varieties of organizations, and varieties of social capital, thereby adding conceptual refinement to the study of network inequality.

Categories, institutions, social capital

Rather than invoke biology, which some see as natural and immutable, a sociological approach to inequality interrogates the role of social arrangements and power relations shaping who gets what in everyday life (Fischer et al., 1996). While gender and ethnicity are well studied as general processes (Tilly, 1998), the unique ways in which they lead to forms of social stratification such as network inequalities remain relatively unexplored. The link that binds ascriptive categorizations and

Gender

Singaporean men have slightly higher levels of access to tertiary education than women; according to the General Household Survey 2005, 34% of men and 26% of women are polytechnic diploma holders or university graduates. Although boys were once privileged in education (because of scarce family resources in a poor society), affluence has, over time, reduced the gender bias. Class background continues to matter for educational attainment, to be sure, but since boys and girls share the same

Varieties of social capital

Scholars have conventionally measured social capital by the extent to which respondents indicate knowing people from a variety of occupations (Lin and Dumin, 1986, Lin and Erickson, 2008). Yet are occupations the only important form of status? Erickson (2001a, p. 324) explains that ‘different aspects of networks are good for different outcomes’; therefore, ‘we need to carefully work out which aspects of networks have which outcomes.’ Although I use the generic term ‘social capital’ to denote

Data sources and measures

The data source is a stratified random sample of 989 Singapore citizens and residents aged between 25 and 55. A reputable research company developed the sample from information supplied by the Department of Statistics. It conducted the survey in three languages, English, Mandarin, and Malay. Each interview lasted about an hour and was conducted at the door of the respondent’s home. The response rate was about 70%. To make up for the non-responses (i.e. could not reach the respondent after three

Gender and ethnic inequality in social capital

Table 2 shows the various types of social capital by gender and ethnic group. The results can be discussed on two levels. At a broad level, we see a general pattern whereby dominant gender and ethnic groups (men and Chinese respectively) have more social capital than their less dominant counterparts (women and minorities respectively).

At the same time, at a more specific level, we see nuanced patterns of network inequalities: women have lower access to such forms of social capital as ties to

Concluding thoughts

Social categories, organizations, class positions, life course patterns, and social capital interface in complicated ways. Interrogating these complexities, this paper aims at a nuanced understanding of the institutional backdrop framing network inequalities in Singapore. By examining network inequalities, this paper responds to Tilly’s (2000, pp. 785) call to ‘move studies of inequality away from wages to other varieties of advantage and disadvantage’.

While social capital tends to be unequally

Acknowledgements

*The 2005 Project Network Survey was supported by the National University of Singapore’s University Research Fund (R-111-000-051-112). Bonnie H. Erickson, Barry Wellman, Zaheer Baber, Eric Fong, Bob Andersen, and Bian Yanjie provided valuable criticisms and suggestions. I thank the four anonymous reviewers for their helpful comments. Elizabeth Thompson provided editorial assistance.

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