Social Networks and Occupational Attainment in

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Social Networks and Occupational Attainment in Australia: A Preliminary Analysis

Xianbi Huang The University of Queensland The University of Queensland Social Research Centre Level 4, GPN3 (Building 39A) The University of Queensland Brisbane, QLD 4072 Email: [email protected] Mark Western The University of Queensland Institute for Social Science Research Level 4, GPN3 (Building 39A) The University of Queensland Brisbane, QLD 4072 Email: [email protected]

Word count: 2673

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Social Networks and Occupational Attainment in Australia: A Preliminary Analysis Abstract: (175 words) Research into social networks and occupational attainment is a well-documented field in economic sociology internationally but has been the subject of little Australian research because of theoretical lack of interest and a shortage of appropriate data. This study attempts to fill this gap by using data from the Australian Survey of Social Attitudes (AuSSA) 2007. We provide two major findings about the role of social networks in Australian occupational attainment. First, as a job search method, social networks are associated with lower earnings and occupational status and lower probability of entering a professional or managerial position than market oriented job search methods. Second, jobs that are found using strong ties such as family members, relatives and friends have lower earnings and occupational status and are less likely to be professional or managerial than jobs found using weak ties such as acquaintances and other people. Although the findings are preliminary, they contribute to international research by using Australian data and drawing out implications for further exploration of the role of social networks in Australia’s labour markets. Key words: Social networks, Occupational attainment, Labour markets, Australia Introduction The role of social networks in labour markets has attracted significant cross-disciplinary attention over the past several decades. Extensive research from Europe, North America, and Asia has shown social networks play a significant part in occupational attainment (Lin, Ensel, and Vaughn 1981; DeGraaf and Flap 1988; Bian 1997; Bian and Soon 1997). So far however there is very little Australian research in this area. Reasons may be two-fold. First, social network analysis, an important branch of economic sociology, has barely registered in Australia. As noted by Gilding (2005), this situation partly arises because economic sociology draws some of its inspiration from “new economy” industries that are weak in Australia, and also because of the influence of the

3 Marxist tradition in Australian sociology, which focuses mainly on the state as a countervailing force to markets and ignores that markets are constituted through social institutions. Second, because of substantive and theoretical inattention, Australian social surveys have not systematically inquired into the field of social networks and labour markets. Thus there is a lack of data about the role of social networks in Australian labour markets. Under these circumstances, it remains unclear whether social networks supplement the market mechanism in occupational attainment or tend to be ineffective as the role of markets increases in Australian employment processes. In order to provide a preliminary analysis of the role of social networks in labour market outcomes, this paper applies the analytical tools of the social network approach and uses newly released data of the Australian Survey of Social Attitudes (AuSSA) 2007 (Phillips et al. 2008). In the following sections, we will first sketch relevant theoretical perspectives and propose propositions. Second, we will describe research methods and data. Finally, we will present research findings and discuss their implications. Theoretical Perspectives and Research Propositions In the study of labour markets, the role of social networks is organised by two main questions, on which a rich literature has developed. The first question is about the comparative effect of social networks versus other job search methods. The classification of job search methods varies somewhat, for example non-personal means versus personal means (Bridges and Villemez 1986), formal channels versus informal channels (Boxman et al. 1991), personal contacts, formal channels and direct application (Lin et al. 1981). Essentially, however across different institutional contexts these job search methods fall into three types: hierarchy, market and networks (Granovetter 1995; Bian 2002). Hierarchical methods of job search refer to job assignments and organised transfers by a state authority or employing organisation. This was the most frequently used method in the state redistributive regime (Bian 1997) but was not merely confined to the socialist economies. In Western societies, organisational reallocations or transfers are also included. Market methods refer to any job search activities in which people are given rights and freedom to individually search out

4 employment, such as attending job fairs where employers gather to recruit employees, using formal employment services, direct applications to employers, responding to media advertisements, online job searches and so on. Network methods refer to any search activities in which personal assistance from others, that is, mobilising social ties and connections, is drawn on to secure employment. Social networks matter significantly for occupational attainment in transitional societies like China and Russia because of institutional insufficiencies in emerging labour markets (Bian 2002; Yakubovich and Kozina 2000) but this underlying logic also suggests that as labour markets approach a “pure form” as in Western societies, social networks will decline in significance as a means to locate better jobs. From a comparative perspective, Australia’s labour market differs greatly from China’s or Russia’s but resembles the Western type. OECD assessments confirm that Australia’s employment protection legislation is one of the least strict among the developed economies (OECD 2003: 100). In 1998, the Australian government announced that the Commonwealth Employment Service (CES) was to be replaced with a nationwide Job Network in which all employment services, including job matching, case management and the delivery of labour market programs, were contracted out to private, community and government organisations. Even by the world standards, the Job Network was a bold policy reform with Australia having one of the most open employment service markets in the advanced world (Dockery 1999). Where market mechanisms are highly developed (encouraged) it is reasonable to expect that social networks will not have an advantageous effect on occupational attainment compared to market mechanisms because of the ostensible optimality of markets in producing efficient matches between jobs and individuals. This leads to: Proposition 1: Social networks are likely to have a less advantageous effect on occupational attainment than market methods. The second question about the role of social networks concerns the relative effects of weak and strong ties on occupational attainment. Ever since Granovetter’s seminal work (1973), a lively debate has occurred about the strength of social ties in job searches. The “strength of weak ties

5 hypothesis” proposed by Granovetter states that individuals are likely to learn nonredundant information about job openings through weak ties of infrequent interaction or of low intimacy because such networks are wide ranging and link individuals across social groups of close interpersonal relationships. This line of inquiry focused on the provision of job information and won wide support in market societies of North America and Europe (Lin, Ensel, and Vaughn 1981; DeGraaf and Flap 1988). In contrast, the “strength of strong ties hypothesis” (Bian 1997) asserts that strong ties of trust and obligation are more advantageous in accessing influence and favour for realising job mobility. Empirical findings from East Asia such as Japan (Watanabe 1987) and Singapore (Bian and Soon 1997) as well as Russia’s transitional economy (Yakubovich and Kozina 2000) have lent support to this hypothesis. Australia’s labour market has experienced considerable change in the past two decades. This reform is part of an international movement, driven by the ideology of free markets and liberal democracy and the competitive pressures unleashed by globalisation (Blandy 2006). Since the early 1990s, the dismantling of the award system has produced a major shift in the institutions of the labour market moving Australia away from a relatively regulated labour market system towards a direct deregulated system (Campbell and Brosnan 1999; Kelsey 1995). Given these changes, Australia’s labour market is closer to counterparts in North America and Europe than East Asia. Social networks are likely to matter more for information transmission than influence or favour. Moreover, due to the “homophily” or “like me” characteristics of social interactions associated with strong ties, they cannot outperform weak ties in collecting job information from various sources and across boundaries of social groups. We therefore suggest: Proposition 2: Strong ties are likely to have a less advantageous effect on occupational attainment than weak ties. Research Methods and Variable Measurements We use data from AuSSA 2007 for our analyses. This national survey was carried out in Australia in 2007 with a sample comprising 6,666 respondents selected at random from the Australian

6 Electoral Roll. Structured self-completed questionnaires were mailed back by 2,781 respondents, yielding a response rate of 42 percent. Because we aim to discover the role of social networks in job search, we exclude cases by respondent’s employment status of current job or last job. Respondents who did not answer or reported that their current job or last job was to work at a family business or farm or self-employed (with or without employees) are excluded from our analyses. Linear regressions and binary logistic regressions are employed for modelling. Below we describe variables. Referring to extant research (Lin et al. 1981; Bridges and Villemez 1986; Boxman et al. 1991), we conceptualize occupational attainment by three dimensions, namely, income, occupational status and professional or managerial position. These are our dependent variables. Income is measured by the response to the following question: “What is your gross annual income before tax/deductions?” Respondents were presented with 14 weekly income intervals. We code income as a continuous variable by assigning the mid point of each interval and then taking the natural log-transformed measures of these values. As shown in Table 1, the average weekly gross income was about 836 dollars. Occupational status is measured by matching respondents’ occupations with the ANU3_2 status scale (McMillan and Jones 2000)1, which is a continuous measure ranging from 0 (low status) to 100 (high status). The mean of the occupational status score in our study approximates 37. Professional or managerial position is a dummy variable, which is based on respondents’ choice from seven major groups of occupations. If “Managers” or “Professionals” were chosen, this respondent is coded to be an occupant of professional or managerial positions. 34 percent of respondents had a professional or managerial position. [Table 1 about here] Independent variables include two social network variables, that is, job-acquisition methods and social ties. The job-acquisition methods variable is constructed from the question “On the whole, which one method was most important for getting your current/last job?” If a respondent chose “I was reallocated or transferred by the organisation I work for”, he/she is treated as using a “hierarchy

7 method”. If a respondent chose “Got help or information from family or relatives”, “Got help or information from friends” or “Got help or information from acquaintances”, he/she is regarded as using “social networks”. If a respondent chose one of the other items, “Looked at media advertisements”, “Used university career services”, “Used an employment agency”, “Used the Internet”, “Approached an employer”, “An employer approached me”, “Other”, or “don’t know”, he/she is coded into the category of using a “market method” (as the reference category). About 4 percent of respondents used hierarchy methods, 18 percent used social networks, and 78 percent used market methods. The coding of social ties is based on the question “Was there one particular person among those who helped you to get this job?” If “friend” or “family member or relative” was chosen, the respondent is regarded as using strong ties (nearly 36 percent). If “acquaintance” or “other” was chosen, the respondent is regarded as using weak ties (about 10 percent). In addition, if the answer was “no”, the respondent is regarded as a no-ties user (about 54 percent). Control variables include demographic variables such as gender, age, years of schooling and university degree. In addition, other characteristics of respondents that might affect occupational attainment are controlled, including union membership, migrant (born overseas) and big-city resident (living in metropolitan areas of a major city over 100,000 people). Their descriptive statistics are reported in Table 1. Findings and Discussion As shown in Table 2, social networks have a significantly less advantageous effect on occupational attainment than market methods, whether examining income, occupational status, or occupying a professional or managerial position. In Model 1, the coefficient of social networks is significant and negative, suggesting that if a job seeker used social networks in securing his/her job, he/she was likely to have a lower income by about 9 percent (1-

.089

) compared to those using market methods.

In Model 3, the coefficient of social networks is significant and negative again, revealing that social networks tend to decrease job seekers’ prospective occupational status by 3 points in the ANU3_2 status scales compared to those using market methods. Moreover, in Model 5, the odds ratio of

8 social networks is .602, smaller than 1, showing that the likelihood of a job seeker in reaching a professional or managerial position is lower by about 40 percent than those using market methods in getting a job. Overall, these findings lend support to Proposition 1 in that social networks have a significantly less advantageous effect than market methods on occupational attainment. Noticeably, hierarchy methods have significant effect on occupational status and entering a professional or managerial position probably because internal transfers commonly entail promotions. [Table 2 about here] The relative effects of strong and weak ties on income, occupational status and entering a professional or managerial position are shown in Models 2, 4 and 6, respectively. Compared to noties users, job seekers using strong ties earn about 8 percent less (1-

.081

), reach an occupation with

a lower status score (about 2.1 points) and have a 30 percent lower likelihood (odds ratio=.707) of obtaining a professional or managerial position. In contrast, weak ties do not have any significant effect on these three dimensions of occupational attainment compared to no-ties users. Consequently, this suggests that Proposition 2 can be accepted. As far as control variables are concerned two human capital variables, i.e., years of schooling and holding a university degree, have significant effects on occupational attainment. In particular, university degree holders have a huge advantage in earning a higher income, winning a higherstatus occupation and entering a professional or managerial position compared to those without a university degree. Regarding gender, men earn significantly higher incomes than women but do not have significant advantages in achieving higher-status occupations or entering professional or managerial occupations. Age has a significant but declining positive effect on three dimensions of occupational attainment. Both union members and migrants are likely to have an occupation with a lower status score; furthermore, union members have a smaller possibility of entering a professional or managerial position compared to those who do not belong to a union. Residents in big cities tend to have higher status occupations than residents in other urban areas.

9 In summary, our research yields two major findings about the role of social networks in Australia’s occupational attainment processes. First, as a job search method, social networks are less advantageous than market methods for attaining occupations with better outcomes. Second, strong ties are less important than weak ties in securing good outcomes. These results are only preliminary since this is an exploratory study. However, it contributes to international research in this field in several ways: first, Australia’s labour markets resemble those in other Western societies in which markets are the dominant means for securing a job, especially for securing a better job in terms of earnings, occupational prestige and an entry to professional or managerial positions. Relatively speaking social networks are overshadowed by market methods. Second, within developed labour markets in Australia, information rather than influence or favour (Granovetter 1973, 1995; Bian 1997) is the most important resource that is conducive to attaining a better occupation. Strong ties held by intimate and homogeneous groups are less useful for transmitting job information than are weak ties linking heterogeneous social contacts. Arguably, the less advantageous effect of social networks on occupational attainment partly reflects the low prevalence of weak ties. As shown in Table 1, more than one third respondents used strong ties but only 10 percent used weak ties. This result suggests that to achieve a better occupation, weak ties that extend social communications and enable access to non-redundant information are better than strong ties. The reason why Australian job seekers opt to mobilise strong ties when looking for jobs remains unconsidered in this study. Future research can advance this issue by further probing into whether social networks serve as a mediating mechanism between personal characteristics (e.g., human capital) and occupational attainment. Third, a promising research agenda may develop by considering what impact will be made on the role of social networks in occupational attainment processes by concrete institutional contexts, like sectoral differentiation, labour market segmentation, industrial relations reform and the like.

10 Note: 1. “ANU3_2 Status Scale” is a recognised occupational status scale for Australia but it is made for the second version of Australian Standard Classification of Occupations (ASCO2). The occupation codes of AuSSA 2007 are based on the first version of Australian and New Zealand Standard Classification of Occupations (ANZSCO1). To construct the occupational status scale for ANZSCO1, we first used the “Correspondence Tables-ANZSCO First Edition to ASCO Second Edition” (ABS 2006) to establish correspondence relationships between these two occupationcoding systems, and then matched ANU3_2 scores to occupations coded by ANZSCO1. For some occupational categories that are partially matched between ANZSCO1 and ASCO2, we calculated the scores by applying a weighted method. For space limit, we do not elaborate details here but they are available upon request.

References Australian Bureau of Statistics. (2006) ABS Cat. no. 1220.0 ANZSCO -- Australian and New Zealand Standard Classification of Occupations, First Edition. Commonwealth of Australia. Bian, Y.J. (1997) ‘Bringing Strong Ties Back in: Indirect Ties, Network Bridges, and Job Searches in China’, American Sociological Review 62: 266-85. Bian, Y.J. (2002) ‘Institutional Holes and Job Mobility Process: Guanxi Mechanisms in China’s Emerging Labor Markets’, pp.117-36 in T. Gold, D. Guthrie and D. Wank (ed.) Social Connections in China: Institutions, Culture, and the Changing Nature of Guanxi. Cambridge: Cambridge University Press. Bian, Y.J. and S. Ang (1997) ‘Guanxi Networks and Job Mobility in China and Singapore’, Social Forces 75: 981-1006. Blandy, R. (2006) ‘Australian Labour Market Reform-What Needs to be Done?’, Australian Bulletin of Labour 32:1-17. Boxman, A.W., P. M. De Graaf, and H. D. Flap (1991) ‘The Impact of Social and Human Capital on the Income Attainment of Dutch Managers’, Social Networks 13: 51-73. Bridges, W. and W. J. Villemez (1986) ‘Informal Hiring and Income in the Labor Market’, American Sociological Review 51: 574-82. Campbell, I. and P. Brosnan (1999) ‘Labour Market Deregulation in Australia: the Slow Combustion Approach to Workplace Change’, International Review of Applied Economics 13:353-94.

11 DeGraaf, N. D. and H. D. Flap (1988) ‘With a Little Help from My Friends: Social Resources as an Explanation of Occupational Status and Income in West Germany, the Netherlands, and the United States’, Social Forces 67:452-72. Dockery, A.M. (1999) ‘Evaluating the Job Network’, Australian Journal of Labour Economics 3: 131-58. Gilding, M. (2005) ‘The New Economic Sociology and its Relevance to Australia’, Journal of Sociology 41: 309-25. Granovetter. M. S. (1973) ‘The Strength of Weak Ties’, American Journal of Sociology 78: 136080. Granovetter. M. S. (1974) Getting a Job: A Study of Contacts and Careers. Cambridge, MA: Harvard University Press. Granovetter. M. S. (1995) ‘Afterword 1994: Reconsiderations and a New Agenda’ in Getting A Job. The University of Chicago Press. Kelsey, J. (1995) Economic Fundamentalism: The New Zealand Experiment - A World Model for Structural Adjustment? London: Pluto Press. Lin, N., W. M. Ensel, and J. C. Vaughn (1981) ‘Social Resources and Strength of Ties: Structural Factors in Occupational Status Attainment’, American Sociological Review 46: 393-405. McMillan, J. and F.L. Jones (2000) ‘The ANU3_2 Scale: A Revised Occupational Status Scale for Australia’, Journal of Sociology 36: 64-80. Organization for Economic Co-operation and Development. (2003) OECD Economics Survey 20022003-Australia, OECD. Paris. Phillips, T. et al. (2008) The Australian Survey of Social Attitudes, 2007. Canberra: Australian Social Science Data Archive, The Australian National University. Watanabe, S. (1987). Job-Searching: A Comparative Study of Male Employment Relations in the United States and Japan. Ph.D. dissertation, Department of Sociology, University of California at Los Angeles, Los Angeles, CA. Yakubovich, V. and I. Kozina (2000) ‘The Changing Significance of Ties: An Explanation of the Hiring Channels in the Russian Transitional Labor Market’, International Sociology 15: 479500.

12 Table 1. Descriptive Statistics of Variables in the Analyses, AuSSA, 2007 Variables Income Gross weekly income (dollar) Gross weekly income (in natural log form) Occupational status Professional & managerial position Job-getting methods Social networks Hierarchy methods Market methods (ref.) Strength of ties Strong ties Weak ties No-tie users (ref.) Control variables Gender (male=1) Age Age2/100 Years of schooling University degree Union membership Migrant Big-city resident

Percent or Mean (S.D.)

Number of cases

835.61 (560.38) 6.44 (.84) 37.48 (20.23) 34.13%

1752 1752 1811 1931

17.98% 4.11% 77.91%

1752 1752 1752

35.49% 10.42% 54.09%

1843 1843 1843

47.77% 48.70 (16.12) 26.32 (16.41) 13.90 (3.69) 27.45% 58.68% 21.46% 62.10%

1752 1752 1752 1752 1752 1752 1752 1752

13 Table 2. OLS Coefficients and Odds Ratios in Predicting Effects of Social Networks on Occupational Attainment, AuSSA 2007 Predictor variables

Job-getting methods Social networks

Income (ln) (OLS model) a

Hierarchy methods Tie strengthb Strong ties Weak ties Control variables Gender Age Age2/100 Years of schooling University degree Union membership Migrant Big-city resident Constant R2 Number of cases

Occupational status (OLS model)

(1)

(2)

(3)

(4)

-.089! (.045) .077 (.087)

-

-3.007** (.975) 4.671* (1.959)

-

-

-.081* (.039) -.013 (.059)

-

-2.063* (.846) -.261 (1.298)

.494*** (.035) .061*** (.006) -.067*** (.006) .037*** (.006) .240*** (.049) .006 (.037) -.052 (.043) .153 (.037) 4.346*** (.169) .261 1752

-

.502*** (.036) .062*** (.006) -.069*** (.006) .036*** (.006) .233*** (.050) .005 (.038) -.055 (.045) .154 (.037) 4.349*** (.177) .261 1682

.214 (.761) .479*** (.129) -.226! (.126) 1.666*** (.133) 17.687*** (1.071) -2.648** (.788) -2.042* (.943) 2.026* (.787) -6.645! (3.691) .391 1811

Notes: 1. The numbers in the parentheses are standard errors. 2. a The reference category is market methods. b The reference category is no-ties users. 3. !p